Inside ECE 2024

2024 Year in Review inside ECE

EDITOR: Catharine June

ECE WRITERS: Mena Davidson, Hayley Hanway

ECE PHOTOGRAPHERS: Jero Lopera, Silvia Cardarelli, Miranda Howard

GRAPHIC DESIGN: Laura Koroncey

We

COVER:

DEAR ECE COMMUNITY,

I am delighted to share the latest accomplishments of our faculty, students, and staff in this year’s edition of Inside ECE.

As Interim Chair of Electrical and Computer Engineering for the 2024-25 academic year, it is rewarding to learn more about the activities of our entire faculty and student body as they create new technology, solve the problems facing society, and advance knowledge for the good of all.

With the recent pandemic further behind us, we have become more accustomed to hybrid schedules and online learning opportunities, and it has been wonderful to see more of each other as we offer more in-person events, some of which you can see pictured in this magazine.

Our faculty are the foundation of our department, and this year we welcome fie new assistant professors. We look forward to their contributions in the areas of computer vision, cyber-physical systems, machine learning and AI, energy storage, HCI, and personalized medical devices.

We are delighted to have three new MURIs based here at Michigan in areas as diverse as social networks, game theory, and ferroelectric materials. These grants have the added benefit of facilitating our patnerships with other institutions. Such collaborations have always been a hallmark of ECE here at Michigan, and around the world.

Our students learn the value of teamwork and understand the interdisciplinary nature of ECE through their coursework, and as they participate in research and student team projects. As Yi Ling Wu, Chief Engineer for M-Fly’s autonomous aircraft, stated: “Yes, it’s an aircraft, but we need EECS expertise for everything inside the aircraft.”

I hope you enjoy learning a bit more about what our faculty and students have been accomplishing this past year, Inside ECE.

JEFF FESSLER

Interim Chair, Electrical and Computer Engineering

William L. Root Distinguished University Professor of Electrical Engineering and Computer Science

Chips for AI

“Machine learning has evolved in the last 10 years to become one of the biggest, most important workloads of integrated circuit design.”

— Prof. Zhengya Zhang

Artificial intelligence (AI) has infiltrated nearly every aspect of modern society. Behind the sleek interfaces of ChatGPT, Alexa, and Ring doorbells are machine learning algorithms that crank through unprecedented amounts of data to deliver answers. The demand for AI at consumers’ fingertips is fueling new hardware solutions to support those applications.

As a result, creative new solutions are required to serve the higher computing demands of AI—solutions that are coming from a diverse, collaborative group of ECE chip designers.

From data centers to edge computing to IoT

Since about 1960, integrated circuit designers have been able to provide more computing power by doubling the number of transistors about every two years. This observed pattern, known as Moore’s Law, is no longer sustainable. Instead, the additional processing power needed for today’s AI applications often comes from high numbers of computers run simultaneously as a network, grouped in clusters or server farms. The financial and envionmental cost of these computing systems is enormous.

There is also a demand for specialized processors to implement and accelerate machine learning in small, low-power devices. The “smart” devices that are increasingly making our lives more convenient are linked together by wireless signals into an accessible network called the Internet of Things (IoT). Within the IoT, edge computing brings the computational work closer to the place where sensors or other devices are gathering the data. The benefits of edge computing include faster response times, improved efficien, and enhanced security—all while reducing network traffic.dge computing has the ability to transform applications in traffic conol, healthcare, supply chain industries, agriculture, and more.

A diverse, collaborative group of ECE researchers are working to combat these challenges and enable efficient sustainable, and accessible AI.

“This is a two-way path,” said Michael Flynn, Fawwaz T. Ulaby Collegiate Professor of ECE. “A lot of the research

at Michigan is using integrated circuits to make efficient AI and machine lear ing possible. But there’s also going to be an impact from machine learning being used for better integrated circuit design.”

Say goodbye to power cords and even batteries

With the slowing of Moore’s Law, researchers shifted from building general, all-purpose processors to domain-specific pocessors like graphics processing units (GPUs). Profits of companies like NVIDIA have skyrocketed due to their popular GPUs and their ability to run large calculations on their cloud facilities. However, running big machine learning algorithms on GPU clusters isn’t the most elegant solution.

“You can build custom silicon chips that are better at executing the types of operations that machine learning requires,” said Dennis Sylvester, the Edward S. Davidson Professor of ECE.

These custom chips, called application specific integated circuits (ASICs), have been used in research and

Edge Computing

industry since the 1960’s, but they now empower researchers to focus on machine learning implementations.

For example, Sylvester is collaborating with David Blaauw, the Kensall D. Wise Collegiate Professor of EECS, and HunSeok Kim, the Samuel H. Fuller Early Career Professor of ECE, to develop ASICs that integrate with sensors to allow devices like voice activated speakers to perform intelligent tasks— all without a power plug.

“From the microphone all the way through the sensor interface and data converter and the back end, through the deep learning layers of the machine learning algorithm, we optimized the whole system,” Sylvester said. “This little system that continuously consumes a microwatt, hears the name Alexa or one of our keywords and wakes up another system that would be in a very deep, lowpower state. Then it would be ready to do natural language processing, answer queries, or anything more complex.”

In another project, Prof. David Wentzloff led a collaboration with Sylvester, Blaauw, and research scientist Mehdi

ECE RESEARCH

Michigan ECE faculty are known for their breakthroughs in ultralow-power circuits and computers, culminating in the world’s smallest computing system, called the Michigan Micro Mote, or M3. Pictured above are the 2014 (left) and 2018 versions of the M3. The 2018 version runs on less than 1 milliwatt.

Saligane to design a system-on-chip (SoC) for an ultra low power wake word application.

“For this project, we leveraged machine learning, but the goal was to reduce the power consumption of the device without compromising its capability,” said Wentzloff.

To completely eliminate the need for a battery, energy can be harvested from renewable sources such as light, heat, vibration, and more. That harvested energy can be stored in sustainable alternatives to batteries called capacitors.

Wentzloff’s desire to get rid of batteries completely led to his development of battery-free sensors used to monitor steam traps in buildings and industrial equipment. “If we enable a world where there’s a trillion batteries out there, I feel like we failed as engineers,” said Wentzloff.

Memory-centric computing

Prof. Wei Lu is looking to meet the ever-expanding requirements for fast AI processing through memory-centric computing.

Photo: Michael Simari

Lab to Market

These startup companies grew out of energy-saving chip technologies developed by ECE faculty.

AMBIQ

Founded by David Blaauw, Dennis Sylvester, and alum Scott Hanson

Ambiq chips have already been deployed in devices like smart watches and rings that monitor aspects of health and fitness.

CUBEWORKS

Founded by David Blaauw, Dennis Sylvester, David Wentzloff, and alum Yoonmyung Lee

CubeWorks sensors have been used to monitor temperature-sensitive healthcare supplies and they are easily deployed in discrete security systems.

EVERACTIVE

Founded by David Wentzloff and colleague Benton Calhoun

Everactive’s first product harvests heat energy to monitor steam traps in buildings and equipment in industrial settings.

Everactiveʼs 2nd generation batteryless industrial monitors are powered by heat or light.

CROSSBAR

Founded by Wei Lu and alum Sung Hyun Jo

Crossbar technology has improved the learning speed of a reservoir computing neural network.

MEMRYX

Founded by Wei Lu and Zhengya Zhang

MemryX's AI chips have been used in a wide range of applications enabling real-time AI inference at the edge.

“In a lot of cases, the performance of the system is limited by the memory rather than the computing itself,” said Lu, the James R. Mellor Professor of Engineering. “That actually has a big impact on research on integrated circuits because previously, the focus was to make the circuits faster. And now the focus is to design circuits that support the memory access. That’s a big paradigm shift.”

One of the most groundbreaking memory applications that Lu has developed is called resistive ram (i.e., RRAM or ReRam), which takes advantage of components called memristors working in parallel to increase computer performance. Memristors store information as resistance in addition to performing computing functions, allowing for energy and space conservation on a computer chip.

Another way to improve both the capacity and energy efficiency o memory modules is to combine computation and storage functions in a circuit. RRAM is perfect for these

architectures, called compute-inmemory, which eliminate the time and energy costs of transporting data between the memory and computation components of an integrated circuit.

In a related project, Sylvester, Blaauw, and CSE Prof. Reetuparna Das are collaborating on a way to convert SRAM memory structures into parallel processing units, allowing convolutional neural networks to be run on conventional chips with small modifications.

“One big advantage of this technique, which we call Neural Cache, is area,” said Das. “Since we are reusing a lot of the memory structures to do compute, you suddenly save a lot of silicon area. All of that area can be used to create more memory, so you can store more machine learning parameters on chip and all sorts of advantages start opening up.”

Brain-inspired computing

The human brain is incredibly efficien at processing sensory information. Humans can automatically locate the direction of a sound, quickly correct

L-R: David Blaauw, Reetuparna Das, Wei Lu, Dennis Sylvester, and David Wentzloff are panelists at Celebrate Invention 2019. Photo: Silvia Cardarelli

balance, and compose images through the visual system in real time. All of these processes and more occur simultaneously in the brain, while consuming only 17–20 watts of power. In contrast, the world’s fastest supercomputer uses 27 megawatts to achieve a similar level of processing.

Many researchers attribute the brain’s efficiencyo the analog nature of its processing and communication, which has researchers turning back to analog computing for AI tasks.

Flynn, Lu, and Zhang are using the brain as inspiration to perform machine learning tasks in edge devices. “The idea is that brains use analog neural networks and they’re super efficient.e’ve built circuits that do sort of what the brain does for image processing,” said Flynn.

By integrating the memristor-based RRAM technology spearheaded by Lu into memory devices, the team developed the first standalone programmable memristor computer in 2019. The team demonstrated the device with three bread-and-butter machine learning algorithms, and it performed with 100% accuracy for two of the three algorithms, and 94.6% accuracy for the third.

In related research, Prof. Robert Dick studies the structure and learning processes of neural networks to improve the efficiency of AI in embedded system like phones and wearable devices. Ideally, he says, these devices should be context-aware so that they can be ready to help you when you need them.

In one project, Dick and his team modeled a computer vision system off of the human biological vision system. While classic computer vision models took a high resolution image of an entire scene and analyzed the whole thing, the human vision system is mainly low resolution, with a small area of high resolution focus.

“It’s this multi-round adaptive system where you capture an image of your environment that’s super low resolution except in a tiny area, and then you determine whether you have enough information to make your decision accurately. If you do, you can stop now and not burn any more energy. If it’s not, then you capture again and add to the information you already gathered,” Dick said. His solution reduced the energy consumption and time by 80%.

The lego blocks of computing

The speedy evolution of AI techniques and applications has made it nearly impossible for integrated circuit designers to keep up.

“The models update every few months,” said Zhang. “IC design usually takes one or two years—so by the time we’re done, the model has already evolved a couple of generations forward, rendering our design ineffective. So how do we actually evolve our hardware design and IC design to catch up with the fast pace of the evolution of machine learning?”

“We’ve built circuits that do sort of what the brain does for image processing.”

— Michael Flynn

The first programmable memristor computer, demonstrated by Wei Lu and colleagues. The team demonstrated that it could run three standard types of machine learning algorithms. Photo: Robert Coelius

ECE RESEARCH

Zhang, Lu, and Flynn are working on a flexible solution that allows them o adapt and update integrated circuit designs as the models progress. Instead of designing large, fied-use circuits, they silo the functions of an integrated circuit into subsystems called “chiplets.” The chiplets may then be integrated like Lego blocks into a larger design and adjusted, reused, and reprogrammed as needed. The team is working with several industry partners to design and produce new chiplets.

AI-designed circuits

The flip side of designing chips o more efficiently handleoday’s AI applications is using machine learning and other AI techniques to aid in the design of chips. ECE researchers are doing that too.

ECE researchers including Saligane and Sylvester have been involved in developing OpenFASoC, short for Open-Source Fully Autonomous Systemon-Chip, which is an open-source tool that can be used to generate simple chip designs. Saligane used this tool to design the chip called MPW-5, which is one of the first open-souce chip designs of its kind. The MPW-5 was quickly followed by successful designs of increasing complexity, called MPW-6 and MPW-7.

“This shows the progress of an open-source tool in an open-source community,” said Saligane. “Everyone is iterating on their designs and doing things that are much more complicated.”

The process is so accessible that high school students assisted with the design of MPW-7, under the guidance of ECE doctoral students Ming-Hung Chen and Anhang Li.

In a related project, Kim has developed a framework to identify the most efficien AI model for a dataset, rather than developing the models manually. “The objective is to not only automatically identify efficient models durin training but also to tailor AI models for seamless integration with customdesigned VLSI processors,” he said.

When his team applied this generalized framework to image classification and large language models, they were able to identify AI models that required 3–4 times less hardware complexity, power usage, and memory footprint for edge devices such as smartphones.

Better algorithms to transform efficiency

This story has focused primarily on the development of chip design approaches to facilitate the demand for AI applications. There are also ECE faculty working to improve the theory and algorithms used in these same applications.

For example, Mingyan Liu, the Alice L. Hunt Collegiate Professor of Engineering, and Prof. Lei Ying are part of a $20M NSF AI-EDGE Institute, led by The Ohio State University, that is working on transforming the efficiency of network

“The Michigan team will be developing theories and algorithms for AIaware networks that deliver the right information at the right time and place to support distributed AI in dynamic, heterogeneous, and non-stationary wireless edge networks,” said Liu.

In another project, Prof. Qing Qu collaborated with Prof. P.C. Ku on a

(L) MPW-5, MPW-6, and MPW-7 chips created with OpenFASoC

Chiplet illustration, Shutterstock

wafer-thin chip-scale spectrometer that is suitable for wearable applications. Qu’s team incorporated machine learning into the device’s operation in order to more efficiently decod the signal emitted from the detector and gather the desired information.

And as a final example, Laura Balzano’s research focuses on getting machine learning models to work more efficiently and seamlessly with existin hardware. This may involve computing with less data, more structured versions of the data, or parallel processing.

“I’m excited to see, over the next 10 years, the strides we make in designing algorithms for hardware and designing hardware to support the algorithms,” Balzano said.

Collaboration, access, and training

The advanced research that ECE faculty are working on to facilitate AI isn’t possible in a silo. Collaborations within the department, the College of Engineering, with other universities, and with industry partners are key to the success of this work.

“Collaboration is becoming so essential that it’s impossible to do our research without it,” Zhang emphasized.

“For me, the most exciting thing about this research is working with a team of students and pulling all these different things together into a demonstration,” said Flynn.

For many researchers, sharing their findings widely and f eely is critical to establishing these collaborations, maintaining consistent research progress, and training the next generation of engineers.

“To facilitate broader experimentation and integration within the research community, we have made our source

code publicly available,” said Kim. “This allows fellow researchers to readily apply, test, and potentially adopt our approach in their own work.”

Even when doing closed source projects, Dick emphasized the importance of decentralizing knowledge around AI and machine learning. “These tools will be very powerful in the future,” he said. “I want to make sure that as these systems become more capable that they are available to normal people and not monopolized and controlled by a very small number of people who are most focused on gathering power.”

Part of distributing new research information to the next generation of engineers happens through formal coursework. In addition to several foundational and introductory undergraduate courses in circuit design and machine learning, ECE faculty offer a range of graduate level courses in these areas.

Through their research and their coursework, ECE faculty are making a real difference ensuring the efficient powerful, and intelligent devices of the future.

“To facilitate broader experimentation and integration within the research community, we have made our source code publicly available.”

— Hun-Seok Kim

A subset of the many U-M ECE graduate students working and collaborating on integrated circuits and machine learning. Photo: Jero Lopera

ECE does AI and ML

The next group of stories offer a glimpse into the research activities going on in ECE related to artificial intelligence and machine learning.

An Array of Research on Machine Learning

ECE researchers presented fourteen papers at the 41st International Conference on Machine Learning (ICML), the leading international academic conference in machine learning.

The problems tackled by faculty and students include transformer & large language models, diffusion generative models, multi-label classification models, non convex optimization, and more. These technical terms are from the play-book for research in GenAI and other information processing applications.

READ ABOUT ALL 14 PAPERS

Here are a few examples of the work presented at the conference.

BANDIT PROBLEMS

Prof. Clay Scott is collaborating with researchers at Boston University and the Indian Institute of Science on bandit problems in machine learning, where the decisions that are being made need to take into account unknown as well as known outcomes. A constrained bandit problem acknowledges the risk that is involved in certain choices being made. For example, clinicians trialing new treatments need to balance the efficacy of the doses with any accompanyin side effects, and along with treatment effica, they may also measure kidney function scores after a treatment.

Scott and his collaborators looked into how to determine the feasibility of using a constrained bandit problem in the first place for a given problem. They see this as a way to extend the applicability of this emerging field.

WHAT CAUSES THE SUDDEN EMERGENCE OF NEW AI CAPABILITIES?

In a collaboration with two Harvard University researchers, doctoral student Ekdeep Singh Lubana and his advisor Prof. Robert Dick studied the causes of sudden emergence of capabilities in generative AI systems. They experimentally demonstrated and explained a new cause: complex capabilities are generally “compositional”—they build on multiple, foundational capabilities. The complex capability only emerges when the model is highly competent in all of the foundational capabilities on which it depends, implying that its accuracy is lower-bounded by the product, not average, of the foundational capabilities.

(a) CelebA concept graph for gender, expression, and hair color. (b) Compositional generalization generative capabilities emerge more slowly for concepts farther from the training set (blue nodes). The key bit vectors indicate the active concepts, i.e., "111" indicates all are active. (c) CelebA dataset had few males, delaying capability to produce male images, especially deeper in the concept graph.

GENAI DIFFUSION MODELS

Research led by Professors Qing Qu and Liyue Shen uncovered new insights into the ability of a generative AI technique known as a diffusion model to produce nearly identical contents even under different training settings. The research could be applied to a better understanding of GenAI techniques, while also being used to safeguard users against adversarial attacks.

“We demonstrated that the generative capability of diffusion models stems from their ability to learn the true underlying distribution,” said Qu.

Diffusion models are trained through a process that begins with sharp, clear images, to which noise is incrementally added, progressively blurring the image and introducing variation. This noise manifests in the images as a grainy pattern, resembling the static seen on an old television set without reception. The core learning mechanism of diffusion models involves reversing this process, systematically removing the noise in a step-by-step “denoising” process to recreate a clear image.

The capacity of various diffusion models to create similar content from the same noise input is recognized as reproducibility. The ECE team has, for the first time, povided a comprehensive study of this phenomenon, showing compelling evidence that diffusion models are superior in learning the underlying data distribution compared to earlier models.

“This will open up many exciting research directions for generative AI in the near future including for medical and scientific applications in general,” said Shen.

For example, by leveraging the reproducibility across different noise levels in diffusion models, it may allow researchers to increase the accuracy and efficiency of other type of generative models, including audio, video, and scientific applications

This research had previously earned the team a Best Paper Award at the NeurIPS 2023 Workshop on Diffusion Models.

Visual content generated with three different diffusion models—DDPMv4, CT, and U-ViT—all trained on the CIFAR-10 dataset. Each image was generated from the same initial noise.

OVERPARAMETERIZATION IN MACHINE LEARNING MODELS

Professors Laura Balzano and Qing Qu, along with their research team, focused on overparameterization, which, simply put, means having more model parameters than found in the training dataset. Overparameterization in machine learning models offers great benefits in terms of optimization and genealization, but it also leads to increased computational requirements as model sizes grow. In this work, the team showed how, by leveraging the inherent low-dimensional structures of data and compressible dynamics within the model parameters, it is possible to reap the benefits of verparameterization without the computational burdens.

This research was selected for oral presentation at ICML 2024.

better performance on few shot fine-tuning (left), finds lower rank solutions (middle), and is more robust to the choice of rank (right) compared to vanilla

Deep LoRA shows

LoRA.

(c) U-Vit

(b) CT

(A) DDPMv4

Better Gen AI Models for Medical Imaging

Professors Liyue Shen, Qing Qu, and Jeff Fessler are working to improve a type of deep generative models known as diffusion models. These models are highly successful in applications such as image generation and audio synthesis, as well as medical imaging and molecule design.

“It is quite exciting to explore the potential of generative models in medical imaging and other scientific disciplines,” Shen said. “I am particularly excited to work on developing new and more efficient diffusion models that ca surpass the current limitations.”

Diffusion models are designed to learn the data distribution, which is important for understanding large-scale and complex real-world data. The team is specifically examining how diffusion models could be applied to inverse problems, which is when a set of observations are used to determine what factors produced the end results.

models are both data-intensive and computationally demanding, which limits their use in many scientific disciplines

“We aim to develop a deeper mathematical understanding of these models to guarantee controllable and trustworthy data generation processes,” said Qu.

This could greatly improve applications such as high-dimensional, high-resolution biomedical imaging, as well as motion prediction based on high-dimensional dynamic imaging.

“We’re

hoping to apply the methods developed in this project to large-scale 3D medical imaging applications, like low-dose X-ray CT and accelerated MRI.”

—

Jeff Fessler

“Generative models are one of the hottest topics in machine learning right now, and I’m excited to have the opportunity to investigate their potential for solving inverse problems, especially in medical imaging,” said Fessler, the William L. Root Collegiate Professor of EECS. “We’re hoping to apply the methods developed in this project to large-scale 3D medical imaging applications, like low-dose X-ray CT and accelerated MRI.”

Currently, there are many limitations regarding the practical applications of diffusion models. In particular, the training and inference of diffusion

Image by QasimAli | Adobe Stock Images

Top to bottom:

Liyue Shen, Qing Qu, Jeff Fessler

How Chatbots Pay Attention

Chatbot users often recommend treating a series of prompts like a conversation, but how does the chatbot know what you’re referring back to? A new study reveals the mechanism used by transformer models—like those driving modern chatbots—to decide what to pay attention to.

“Let’s say you have some text which is very long, and you are asking the chatbot to identify key topics, to aggregate and summarize them. In order to do this, you need to be able to focus on exactly the right kinds of details,” said Prof. Samet Oymak. “We have mathematically shown for the first time how tansformers learn to do this.”

Transformer architectures, first proposed in 2017, revolutionized natural language processing because they are so good at consuming very long strings of text—GPT-4 can handle whole books. Transformers break the text up into smaller pieces, called tokens, that are processed in parallel yet hang onto the context around each word. The GPT large language model spent years digesting text from the internet before springing onto the scene with a chatbot so conversant it could pass the bar exam.

The key to transformers is the attention mechanism: they decide what information is most relevant. What Oymak’s team found is that part of a transformer’s method for doing this is pretty old-school—they’re basically using support vector machines invented 30 years ago. An SVM sets a boundary so that the data falls into one of two categories. For instance, they’re used to identify positive and negative sentiment in customer reviews. It turns out that transformers are doing something similar in deciding what to pay attention to—and what to ignore.

Although it sounds like you’re talking to a person, ChatGPT is actually doing multidimensional math. But as to how it works scientifically—no one was quite sure. It all happened in the socalled “black box” of machine learning algorithms.

“We don’t understand what these black box models are doing, and they are going mainstream,” Oymak said. “This is one of the first studies o clearly show how the attention mechanism can find and retrieve a needle of useful information in a haystack of text.”

The team intends to use this knowledge to make large language models more efficient and easiero interpret, and they anticipate that it will be useful for others working on aspects of AI where attention is important, such as perception, image processing and audio processing.

“This is one of the first studies to clearly show how the attention mechanism can find and retrieve a needle of useful information in a haystack of text.”

— Samet Oymak

“Wouldn’t you rather have AI that doesn’t make errors and is fairer in making decisions that could impact your life?”

— Alfred Hero

Reducing AI Hallucinations

From helping researchers identify promising solutions to teaching children critical thinking skills, generative models like ChapGPT are revolutionizing how the world uses and understands data—but there are limitations.

“If you train an image classifier on cats, it’s probably not going to be very good at classifying dogs,” said Alfred Hero, the John H. Holland Distinguished University Professor of EECS and R. Jamison and Betty Williams Professor of Engineering.

To solve this problem, Hero and group members Zeyu Sun (doctoral student) and Dr. Dogyoon Song developed a new method of recalibrating pre-trained neural networks for different domains, which greatly improves their applicability and reduces the risk of AI hallucinations. An AI hallucination refers to faulty information that is presented as fact by a generative AI program such as ChatGPT.

“With our algorithm, practitioners can use a lot more data, even when it’s collected from different types of

modalities under different conditions,” Hero said. “The resulting predictive model will be more accurate and reliable.”

One specific scenario Heo’s team considered was predicting the likelihood of solar flaes, which are large eruptions of electromagnetic radiation from the Sun that can disrupt satellite operations, radio communications, and power grids.

Hero’s team used data from two different generations of satellites to train a solar flae prediction model. Before being retired several years ago, the previous generation satellite had collected substantial data from years of tracking sunspots and their correlation with sun flae activity. The new satellite had collected less data, but the measurements were more accurate and the labels had evolved to better describe recent trends in sunspot cycles and intensities.

“Whatever your feelings are on AI, the reality is that it’s here to stay,” Hero said. “Wouldn’t you rather have AI that doesn’t make errors and is fairer in making decisions that could impact your life?”

PhD student Zeyu Sun (left) and Research Fellow Dogyoon Song presented the research at NeurIPS 2023 as a spotlight poster.

OptoGPT to Design Solar Cells, Smart Windows, and Much More

Professor Jay Guo developed a new technique that he is calling OptoGPT; it’s modeled after the more familiar ChatGPT, and operates along similar principles. More specificall, OptoGPT harnesses the computer architecture underpinning ChatGPT to work backward from desired optical properties to the material structure that can provide them. Manufacturers of solar cells, telescopes, and other optical components may be able to design better devices more quickly with this technique.

Known as an inverse design algorithm because it starts with the desired effect and works backward to a material design, OptoGPT offers more flexibility than previous inverse design algorithm approaches, which were developed for specific tasks.

The new algorithm designs optical multilayer film structues—stacked thin layers of different materials—that can serve a variety of purposes. For example, well-designed multilayer structures can maximize light absorption in a solar cell or optimize reflection in a telescope. They can improve semiconductor manufacturing with extreme UV light, or make buildings better at regulating heat with smart windows that become more transparent or more reflectie depending on temperature.

OptoGPT produces designs for multilayer film structues within 0.1 seconds, almost instantaneously. In addition, OptoGPT’s designs contain six fewer layers on average compared to previous models, meaning its designs are easier to manufacture.

“Designing these structures usually requires extensive training and expertise as identifying the best combination of

materials, and the thickness of each layer, is not an easy task,” said Guo.

For someone new to the field, its difficul to know where to start. To automate the design process for optical structures, the research team tailored a transformer architecture—the machine learning framework used in large language models like OpenAI’s ChatGPT and Google’s Bard—for their own purposes.

“In a sense, we created artificial sentences to fit the existing model structure,” Guo said.

“In

a sense, we created artificial sentences to fit the existing model structure.”

— Jay Guo

New MURI Links Online and Offline Social Networks

Prof. Lei Ying leads a new Multidisciplinary University Research Initiatives (MURI) project that seeks to develop nonlinear, multi-scale, multi-network models to understand how the interplay between online networks (such as social media and other online communities) and offline networks ca impact real world behaviors and events.

“We want to apply machine learning, data science, and AI tools—which have revolutionized computer science—to the social sciences,” Ying said. “Having new mathematical models and machine learning tools to understand how online and offline networks impact each oth, we can better predict disruptive human behaviors.”

Until recently, the study of human social networks has largely been segregated by type: offline in person networks vs onlin social communities. However, understanding the interaction and inuence between these types of networks could greatly help social scientists predict events that lead to unrest, including violence and political upheaval.

“By understanding how online networks impact offline bevior and vice versa, we can develop better interventions,” Ying said. “For instance, what’s the best solution when false information is spreading? Is it better to provide truthful information or to try and limit the spread of misinformation? What kinds of policies would be most effective?”

While there has been much attention to the spread of conspiracy theories and the normalization of politically extreme opinions online, there are no robust mathematical models and analytical tools to explain how this might

impact real world events. This has led to inaccurate assumptions about the role online communities play in offlin movements.

For example, many assume that online activity triggers real world activism events, but this has yet to be proven, and existing research suggests the connection is more complicated. For instance, studies on the Arab Spring showed social media use to be the result of offline attitudes and activities,ather than the cause.

“Online networks may not be the origin for real world behavior, but because they can spread information so fast, they can have a big impact on how these events play out,” Ying said. “The event probably would have happened regardless, but online networks mean the event could be on a much bigger scale, and therefore a lot more disruptive.”

The MURI, titled “Understanding Social Network-Transcendent Online/Offlin Behavioral Dynamics: From Data to Models to Prediction,” aims to develop a mathematically robust model that captures this interplay between online and offline networks, and how ty could impact disruptive behavior and events.

“We want to apply machine learning, data science, and AI tools—which have revolutionized computer science—to the social sciences.” — Lei Ying

Quantum-inspired Computational Imaging

Research that was described in a 2018 Science article has been recognized with the inaugural Best Paper Award in Theoretical Computer and Information Sciences, and it came with a $25K monetary award.

The article “Quantum-inspired computational imaging” describes imaging techniques that will one day: allow doctors to more safely view tumors deep inside the body; facilitate images of objects that are out of sight, far away, or in extremely low light; or improve automobile safety for both drivers and pedestrians.

The award is shared by the international team of Alfred Hero, the John H. Holland Distinguished University Professor of EECS, Yoann Altmann and Stephen McLaughlin (Heriot-Watt University, Scotland), Miles Padgett (University of Glasgow, Scotland), Vivek Goyal (Boston University, US), and Daniele Faccio (University of Glasgow).

This team came together to describe the variety of approaches they had taken in their own research, and the impact on the research community was immediate, and lasting.

Hero described the research:

This is the first published work that describes the promise of using quantum-inspired single photo detection coupled with computation for imaging in situations that were not possible in the past. The crux of the method is to capture light in flight dynamically as each photon falls on the detector. The method is designed to work when the target is illuminated by a laser light source at very low intensities.

Some promising applications are in security, urban safety, space, and medicine.

The technology allows us to take images of objects when there is no line of site between the illumination source and the object, allowing us to, for example, see around corners or to perform 3D imaging from a single source. It is also possible to reconstruct objects that are very far away. A recent article described an experiment where they were able to image a small object at a distance of 50 km (~30 miles). This is extremely low light imaging. These open up potential applications to security and safety. As one example, the technology can be incorporated into automobiles to quickly detect unsafe situations, such as obstacles with low light reflectivit, or an around the corner vehicle who is about to run a red light.

In space, the technology is already being used for satellite telemetry and high resolution imaging of celestial objects, e.g., detailed topographical imaging of the moon and planets in the solar system.

Another emerging application is medical imaging using pico-second resolved low intensity single photon laser scanning to avoid damaging tissue. For example, single and two photon laser imaging technologies have been recently proposed for non-invasive, cellular-resolution retinal imaging and skin cancer screening.

Key advantages to this technology are its compact size, low energy requirements, high resolution, and non-line-of site detection capabilities—enabled by the computational techniques that are employed.

Right now, the bottleneck is not the computation; we have that largely figued out. The main issue now is with the SPAD [single-photon avalanche diode] technology, which is used for single photon counting and timing. These devices have existed since about 2005, but they need to get much better from an energy consumption, photon collection efficien, noise rejection, and timing resolution standpoint.

Some systems are starting to appear, like single photon lidar systems for autonomous driving, where you need split second timing accuracy and fast 3D image acquisition time. I think we’re now within 5 years of seeing some pretty amazing new imaging technologies result from this quantum-inspired marriage of photo-detection and computation.

Image conveying low intensity multiple photon beams

How Green is Green Technology?

P“Green technologies may not always be green in practice.”

— Johanna Mathieu

rof. Johanna Mathieu focuses on ways to reduce the environmental impact, cost, and inefficiency of electric power system through new operational and control strategies. One way she has tackled this is to use the HVAC systems in buildings; this research is described more on page 33. She has also been evaluating the impact of integrating battery storage into electrical grids. However, the economics behind electrical grid reliability complicate the impact, requiring more careful implementation to ensure reduced emissions.

“Green technologies may not always be green in practice. We need to understand these complicated interactions to assess tradeoffs and also to develop deployment strategies that match our goals,” said Mathieu.

In collaboration with public policy Prof. Catherine Hausman, Mathieu has been exploring the impact of changes in electricity reliability markets—often referred to as ancillary services markets—on electricity generation

markets, affecting the mix of resources on the grid and associated greenhouse gas emissions.

“We argue that power plants should be considered multi-product firms” said Hausman. “Focusing on either the electricity generation or reliability market might lead to incorrect or incomplete conclusions about plant behavior.”

The team studied real electricity market data from PJM, the largest Regional Transmission Organization in the U.S., to analyze the spillovers between the two markets, or the impact of one on the other. They found that between 2012 and 2014, changes in the need for grid reliability services changed the mix of power sources providing energy in the electricity market. Specificall, a reduced need for grid reliability services, which is comparable to the addition of batteries, increased emissions as the power generation market shifted to favor the more CO2-intensive coal over natural gas. While increased emissions is not always the outcome, it should be considered when implementing batteries to maintain grid reliability.

Previous simulation-based engineering research assessed the impact of battery integration on greenhouse gas emissions, but this analysis is the first o use real data and incorporate methods from economics.

“Integrating engineering and economics methods and insights generated a much deeper understanding of this problem than if we had worked on this problem in our own silos,” said Mathieu.

As electrical grids continue to integrate renewable energy sources and energy storage, this research can inform policy by working to design the system and operations to ensure battery storage has a positive impact.

A Low-Cost Solution for Impaired-Driver Tech

Drunk driving remains one of the leading causes of death on America’s roads. In 2021, the National Highway Traffic Sety Administration (NHTSA) reported 13,384 deaths were linked to drunk driving—up 14% from the previous year. The agency estimates an average of 37 people die each day in drunk driving accidents.

in newer model cars, combined with facial recognition tools. This system could effectively detect drunk, drowsy or distracted drivers before they get on the road—or while they are on the road.

“You can see these 3D camera technologies in products like smartphones, tablets and mixed reality devices,” said Islam. “In many new vehicles, Advanced Driver Assistance Systems (ADAS) cameras are already onboard to track driver alertness. They’ve already been matured and are cost-effective.”

Islam’s team proposes augmenting existing ADAS cameras with infrared Light Detection and Ranging (LiDAR) or structured light 3D cameras costing roughly $5–$10. Their proof of concept experiments, which interpret data captured by the 3D cameras with artificial intelligence ools, can identify fie signs that a driver may be impaired: 1) increased blood flow o the face; 2) heart rate; 3) eye behavior; 4) head position and body posture; and 5) respiratory rate.

The team demonstrated that the system can measure vital signs, detect drowsiness and provide data that correlates with breathalyzer readings. The researchers are now working with Tier 1 auto suppliers, including DENSO, and Tier 2 suppliers that make the cameras to further develop and potentially commercialize the technology.

The technology was developed with support from DENSO and Islam’s company, Omni Sciences.

“You can see these 3D camera technologies in products like smartphones, tablets and mixed reality devices.”

— Mohammed Islam

Thanks in part to the efforts of Michigan U.S. Representative Debbie Dingell, there is a new federal requirement for all new passenger vehicles to be equipped with the technology to help safeguard against drunk and impaired driving. The requirement passed as part of the 2021 Infrastructure Investment and Jobs Act, and the deadline could come as soon as 2026.

Prof. Mohammed Islam believes he has a low-cost solution that could meet this deadline. The technology would use cameras similar to those already present

Mohammed Islam holds a prototype development kit of a hybrid camera (top) and a ‘direct time of flight’ sensor (bottom), a sensor found in smartphone cameras for proximity sensing. Photo: Jeremy Little, Michigan Engineering

The system aims to detect drunk, drowsy and distracted drivers by looking for five signs that can be observed from the driver’s face and body. Image: Michigan Engineering

Rethinking Game Theory in Dynamic Environments

Michigan ECE is taking the lead on improving our understanding of how humans interact with semiand fully-autonomous artificial intelligence systems through a $7.5M, fie-year Multidisciplinary University Research Initiatives (MURI) called New Game Theory for New Agents: Foundations and Learning Algorithms for DecisionMaking Mixed-Agents.

“There are lots of different agents that are interacting, including the usual players humans which could be big entities, like corporations, governments, or other institutions,” explained project leader Vijay Subramanian. “But in today’s world, we have these new AI agents as well. What we want to understand is: how do these computational agents interact?”

Game theory models how individuals strategize and make decisions, either collaboratively or competitively. Each player should attempt to maximize their progress toward an individual or shared goal, using the information available to them. This information could include the rules of the game such as in poker, Go, or trading in the stock market as well as any knowledge about the other players’ goals or intentions. When none of the players can improve their outcomes by changing their decisions alone, the game has reached a state called equilibrium.

Over several decades, researchers in economics, mathematics, computer science, engineering, and even biology have developed game theory to predict the outcomes and equilibria of various scenarios. Now,

AI systems are overtaking humans in their ability to quickly handle and process huge amounts of data, adding an element of the unknown into these assessments.

“Our [MURI’s] goal is to… develop new theory that can address this mixture of autonomous, semi-autonomous, algorithmic, and human agents.”

— Vijay Subramanian

“The existing theory makes very stringent assumptions on the computing or reasoning capabilities of agents and the AI agents that I mentioned need not have all of those,” said Subramanian. “Our goal is to transcend that and develop new theory that can address this mixture of autonomous, semiautonomous, algorithmic, and human agents.”

One real-world example of a scenario that would benefit fom this type of analysis is the rescue and cleanup operations in a disaster zone say, after an earthquake or airstrike. In a modern disaster zone, humans may work together with robots to clear debris from the area and provide medical care to injured survivors.

Other examples of modern multiagent systems include combatting poachers; assessing the likelihood of and thereafter preventing systemic failures in the financial system, like the Great Depression (1930s) and the Great Recession (2000s); and deploying fleets of automated cars.

The research will be conducted with MURI collaborators at Yale University, Toyota Technological Institute Chicago, University of Southern California, Massachusetts Institute of Technology, Harvard University, California Institute of Technology, and Cornell University.

One scenario that could use Subramanian’s applied game theory is the cleanup of a disaster zone, where humans and AI robots must work together and communicate efficiently.

Exploring Specialized Ferroelectrics

Anew type of ferroelectric semiconductor could enable data storage in hightemperature environments, as well as accelerate quantum computing. Michigan ECE is leading the development of new materials and devices to demonstrate these improved capabilities through a $7.5M, fie-year Multidisciplinary University Research Initiatives (MURI) entitled NanoTOP: Nanoscale and TransductionOptimized Pristine Ferroelectrics.

“One major aspect of this MURI is to study some of the basic issues of these newly discovered semiconductors, which can potentially lead to next-generation microelectronic devices and circuits operating at incredibly high temperatures and speeds and with much reduced size and improved efficien,” said project leader Zetian Mi.

The researchers will produce these semiconductors by incorporating rare earth elements into commonlyused semiconductor materials like gallium nitride or aluminum nitride. When the rare earth element is added, the fied polarization of the material becomes switchable, controlled by the application of an electric field o the material. This allows the efficient orage of data in the polarization state, even when the device is switched off or the electrical field is emoved.

The MURI team aims to enhance the nonlinear optical properties and stability of the ferroelectric material, while reducing its energy loss and the electric field intensity required to switch the polarization

Zetian Mi (L) and Mack Kira discuss their work in the laboratory. Photo: Jero Lopera

“One

major aspect of this MURI is to study some of the basic issues of these newly discovered semiconductors, which can potentially lead to next-generation microelectronic devices and circuits.”

— Zetian Mi

“This material has the potential to enable a quantum transduction for quantum photonic integrated circuits that will be able to convert light efficiently om ultravioletvisible to infrared, as is needed to

flexibly connect futue quantum computers and sensors,” said Mi.

“These quantum mechanisms can be optimized to potentially switch memories at the clock speed of a light oscillation, enabling lossless ultrafast transitions between electronic states essential for next-generation AI and quantum applications,” added Prof. Mack Kira.

The research will be conducted with MURI collaborators Manos Kioupakis and Robert Hovden at Michigan, as well as researchers at Ohio State University, Georgia Institute of Technology, Pennsylvania State University, and Yale University.

“It is extremely exciting to work with such a crossdisciplinary team that allows our systems to connect sensing in the wild to understanding viruses.”

— Pei Zhang

Pre-pandemic Planning

Many of the contagious illnesses that emerge to plague humans, such as H5N1 “bird flu” originate from animal hosts. A new seven-year, $18M U.S. National Science Foundation Center for Pandemic Insights (NSF CPI) aims to develop research and technology for the detection of outbreaks of disease. Michigan is one of 10 institutions involved in the UC, Davis -led center, thanks to the participation of Prof. Pei Zhang and his group.

“It is extremely exciting to work with such a cross-disciplinary team that allows our systems to connect sensing in the wild to understanding viruses,” said Zhang.

The center will use sensing technology to detect key events that precede pandemics, starting with monitoring of animal populations. Zhang will contribute a network of sensors to

record the movement of animals, detect disease cycles, and measure features of the environment such as weather and local topography. His research team will use this information to develop multilevel models of animal space use, an important aspect of disease spread and pandemic risk.

Zhang’s research group is well-suited to this task. He has previously used GPS and proximity sensors to track the movement and social behavior of wild zebras in Kenya. He has also employed vibration sensors to record the maternal behavior of sows toward piglets, predict health risks or emergencies for elderly care home patients, and identify early signs of rare degenerative disease in children. His work at CPI will extend these methods to study pandemics.

The CPI partnerships, which include Labyrinth Global Health and the San Diego Zoo Wildlife Alliance, are strategically set up to bring new insights into the pre-emergence phase of pandemics, transform researchers’ ability to study them, and enable safe and efficient monoring for emerging diseases globally.

A zebra wears a mobile sensor, and Pei Zhang reviews data from his project measuring behavior in sows.

Radar Vision for Indoor Robots

Aline Eid has been awarded a grant from the Michigan Translational Research and Commercialization (MTRAC) Advanced Transportation Innovation Hub to support her research on radar vision for autonomous robots and drones. The technologies she develops will be marketed in collaboration with the startup Atheraxon in an $8B serviceable market for autonomous guided vehicles (AGVs).

“It is incredibly difficult for aomated systems to precisely locate themselves in space,” said Eid. “This multi-billiondollar problem is stifling the gowth potential of hundreds of industrial robotics companies by setting the starting cost of their robots above tens of thousands of dollars per unit and limiting their appeal to niche markets.”

Many warehouse tasks are good candidates for automation, due to monotony or hazardous conditions for human workers. A large majority

of supply chain professionals view warehouse automation as a positive innovation for the industry, with 75–77% of organizations planning to automate some of their warehouse processes in the next three years. However, as of 2021, only 6% of warehouses had deployed AGVs due to financial or logistical limitations.

“Our solution introduces a radar technology to the robotics space that enables a 10X lower cost and fully dependable new solution to this problem,” Eid said. “The very first introduction of this new and cutting-edge radar technology to the robotics space has the potential to radically enhance the abilities of rolling, walking, and flying robotics platforms in indoor facilities.”

Eid’s team will sell the patented technology and process including the radar module and a SLAM algorithm for the radar equipment to companies that design and manufacture AGV robots as a customized solution.

“It is incredibly difficult for automated systems to precisely locate themselves in space.”

— Aline Eid

The technology can help automate tasks such as forklift operation, inventory, loading and unloading pallets or conveyer belts, and transporting items throughout the warehouse. Automating these tasks allows them to be done more quickly and reduces error, while keeping human workers safe from falls and injuries. Together, these benefits can make global supply chains more stable, efficient, andeliable.

A virtual demonstration shows a robot navigating through a warehouse with labeled shelving units and robot workers. Image courtesy Aline Eid.

Better Night Vision Goggles with OLEDs

N“One of the most attractive features of this new approach is that it amplifies light within a thin film stack that is less than a micron thick.”

— Chris Giebink

ight vision systems are due for an upgrade, which can be accomplished by adopting new techniques being developed by Prof. Chris Giebink in his Applied Optoelectronics and Photonics Lab. A new type of OLED (organic light emitting diode) could replace the typically bulky night vision goggles with lightweight glasses, making them cheaper and more practical for prolonged use.

A memory effect in the OLEDs could also lead to computer vision systems that both sense and interpret incoming light signals and images.

Current night vision systems rely on image intensifiers that conert incoming near-infrared light into electrons, which then accelerate through a vacuum into a thin disc containing hundreds of tiny channels. As they pass through and collide with the channel walls, the electrons release thousands of

additional electrons and go on to strike a phosphor screen, which converts them into visible light. The incoming light is amplified y 10,000 times in this process, allowing the wearer to see at night.

The newly developed OLED device also converts near infrared light into visible light and amplifies it moe than 100 times, but without the weight, high voltage and cumbersome vacuum layer required for traditional image intensifiers. A much higher amplificatio is possible by optimizing the design of the device.

“One of the most attractive features of this new approach is that it amplifies light within a thin film stack that is less than a micron thick. That’s much thinner than a strand of hair, which is about 50 microns thick,” said Giebink.

And because the device operates at much lower voltage than a traditional image intensifie, it opens the door to significantly educing power consumption and thereby extending battery life.

The new and improved device also exhibits a sort of memory behavior that could have applications in computer vision. Known as hysteresis, its light output at a given moment depends on the intensity and duration of past input illumination. The ability to remember past inputs could make these OLEDs a good candidate for the type of neuronlike connections that enable an input image to be interpreted and classified without having to process the data in a separate computing unit.

The technology is patent-pending by OLEDWorks and Penn State University, where the study originated before Giebink moved to U-M.

ECE Postdoc Raju Lampande demonstrates the new night vision OLED in Prof. Giebink's lab. Photo: Marcin Szczepanski, Michigan Engineering.

We Now Have Blue for Efficient OLED Lighting

Lights could soon use the full color suite of perfectly efficient ganic light-emitting diodes, or OLEDs, that last tens of thousands of hours, thanks to an innovation that came out of Prof. Stephen Forrest’s Optoelectronic Components and Materials Group.

“Achieving long-lived blue PHOLEDs has been a focus of the display and lighting industries for over 20 years. It is probably the most important and urgent challenge facing the field of oganic electronics,” said Forrest, the Peter A. Franken Distinguished University Professor.

His group’s new phosphorescent OLEDs, commonly referred to as PHOLEDs, can maintain 90% of the blue light intensity for 10-14 times longer than other designs that emit similar deep blue colors. That kind of lifespan could finally make blue PHOLEDs hardy enough to be commercially viable in lights that meet the Department of Energy’s 50,000-hour lifetime target. Without a stable blue PHOLED, OLED lights need to use lessefficient technologyo create white light.

The lifetime of the new blue PHOLEDs currently is only long enough to use as lighting, but the same design principle could be combined with other lightemitting materials to create blue PHOLEDs hardy enough for TVs, phone screens and computer monitors. Display screens with blue PHOLEDs could potentially increase a device’s battery life by 30%.

PHOLEDs have nearly 100% internal quantum efficien, meaning all of the electricity entering the device is used to create light. As a result, lights and display screens equipped with PHOLEDs can run brighter colors for longer periods of time with less power and carbon emissions.

Prior to this research, the best blue PHOLEDs weren’t durable enough to be used in either lighting or displays. Only red and green PHOLEDs are stable enough to use in devices today, but blue is needed to complete the trio of colors in OLED “RGB” displays and white OLED lights. Red, green and blue light can be combined at different relative brightness to produce any color desired in display pixels and light panels.

“A lot of the display industry’s solutions are upgrades to fluoescent OLEDs, which is still an alternative solution,” said doctoral student Haonan Zhao. “I think a lot of companies would prefer to use blue PHOLEDs, if they had the choice.”

“Achieving

long-lived blue PHOLEDs… is probably the most important and urgent challenge facing the field of organic electronics.”

— Stephen Forrest

Haonan Zhao and Claire Arneson fabricate blue PHOLED devices in the lab. Photo: Miranda Howard

ZEUS: A Grand Opening

After four years of constructing what will be the most powerful laser system in the U.S., the team took a moment to celebrate the opening of the zettawatt-equivalent ultrashort pulse laser system (ZEUS) facility with a public event on October 16, 2023.

“At this milestone, we want to honor the people who designed and built the laser system, as well as those who made the lab space ready and built the systems that ensure that the laser is safe to operate. This celebration also expresses our gratitude for the support of the National Science Foundation (NSF), which funded the building and now the operation of the laser system,” said ECE Prof. Louise Willingale, Associate Director of ZEUS.

Distinguished University Professor Emeritus Gérard Mourou. He developed the method for amplifying laser pulses employed by ZEUS and scaled it up at U-M, launching the university as a leader in the technique.

“We came with the idea to build high intensity lasers. And what we dreamed 35 years ago is what is existing now. This was a really incredible gift for me,” said Mourou.

Very soon, the ZEUS team will be ready to run its signature experiment. They will split the beam in two, use part of it to create a beam of electrons traveling at nearly the speed of light, and then run those electrons into the laser pulse. For the electrons, the laser pulse will seem a million times more powerful than three petawatts—enabling researchers to find out what zettawatt laser pulses can do.

ZEUS is designed to lead the U.S. with a peak power of three petawatts—about a thousand times the electricity consumption of the whole world, but for a few quintillionths of a second. It is open to external researchers who want to probe the quantum laws underpinning reality and explore new ways to generate X-ray and particle beams. The findings could advance healthcare and microelectronics, provide insights into extreme astrophysics, and more.

The ceremony included remarks from Nobel laureate and A. D. Moore

ECE research scientists John Nees, Anatoly Maksimchuk, and Paul Campbell assisted with the tours of the ZEUS facility. Nees has been leading the ZEUS laser construction; Maksimchuk has been leading development of the experimental areas; and Campbell has been instrumental in preparing the solid target area.

One of the capabilities that the team is most excited about is the ability to get very precise laser pulses through the use of deformable mirrors in the target areas. These can make up for imperfections in the myriad optical components in >1,000 ft. long path that the laser pulses take.

Gérard Mourou at the grand opening. Photo: Daryl Marshke

Deformable mirror, Gérard Mourou in background. Photo: Daryl Marshke

Rick Van Camp, Laboratory Engineer, next to a diffraction grating. Photo: Daryl Marshke

Designing Chips for Efficient AI Processing

I“Right now, there’s a lot of interest in AI, but to process bigger and more interesting data, the approach is to increase the network size. That’s not very efficient.”

— Wei Lu

n the latest advancement using memristors for efficient memy processing, Prof. Wei Lu teamed up with an interdisciplinary and multiinstitutional group of faculty to develop the first memrisor with a so-called relaxation time. With this feature, artificial neual networks may soon be able to process time-dependent information, such as audio and video data, 6x more efficiently than is possibl in current systems.

Memristors, electrical components that store information in their electrical resistance, could reduce AI’s energy needs by about a factor of 90 compared to today’s graphical processing units. Already, AI is projected to account for about half a percent of the world’s total electricity consumption in 2027, and that has the potential to balloon as more companies sell and use AI tools.

“Right now, there’s a lot of interest in AI, but to process bigger and more interesting data, the approach is to increase the network size. That’s not very efficien” said Lu, the James R. Mellor Professor of Engineering.

The problem is that GPUs operate very differently from the artificial neual networks that run the AI algorithms—the whole network and all its interactions must be sequentially loaded from the external memory, which consumes both time and energy. In contrast, memristors offer energy savings because they mimic key aspects of the way that both artificial and biological neural networks function without external memory. To an extent, the memristor network can embody the artificial neual network.

While Lu’s group had explored building relaxation time into memristors in the past, it was not something that could be systematically controlled. But now, the team, co-led by Lu and materials science and engineering Prof. John Heron, has shown that variations on a base material can provide different relaxation times, enabling memristor networks to mimic this timekeeping mechanism.

The team built the materials on the superconductor YBCO, made of yttrium, barium, carbon, and oxygen. These memristors were made through an energy-intensive process because the team needed perfect crystals to precisely measure their properties, but they anticipate that a simpler process would work for mass manufacturing.

“So far it’s a vision, but I think there are pathways to making these materials scalable and affordable,” Heron said. “These materials are earth-abundant, nontoxic, cheap, and you can almost spray them on.”

The 14-member team also included Prof. Emmanouil Kioupakis, faculty from Cornell University and Pennsylvania State University, and graduate students. The device was built in the Lurie Nanofabrication Facility and studied at the Michigan Center for Materials Characterization.

Nextgen Computing with Quasiparticles

Anew kind of “wire” for moving excitons could help enable a new class of devices, perhaps including room temperature quantum computers. What’s more, the team, led by Profs. Parag Deotare and Mack Kira, observed a dramatic violation of Einstein’s relation, used to describe how particles spread out in space, and leveraged it to move excitons in much smaller packages than previously possible.

“Nature uses excitons in photosynthesis. We use excitons in OLED displays and some LEDs and solar cells,” said Deotare. “The ability to move excitons where we want will help us improve the efficienc of devices that already use excitons and expand excitonics into computing.”

An exciton can be thought of as a particle (or quasiparticle), but it’s really an electron linked with a positively-charged empty space in the lattice of the material (a “hole”). Because an exciton has no net electrical charge, moving excitons are not affected by parasitic capacitances, which are electrical interactions between neighboring components in a device that causes energy losses. Excitons are also easy to convert to and from light, so they open the way for extremely fast and efficient computers that use combination of optics and excitonics, rather than electronics.

This combination could help enable room temperature quantum computing, said Kira. “Full quantum-information applications remain challenging because degradation of quantum information is too fast for ordinary electronics,” added Kira. “We are currently exploring lightwave electronics as a means to supercharge excitonics with extremely fast processing capabilities.”

The lack of net charge also makes excitons very difficulto move. Previously, Deotare had led a study that pushed

excitons through semiconductors with acoustic waves.

In this research, a pyramid structure enables more precise transport for smaller numbers of excitons, confined to one dimension like a wire. They also showed experimentally that a wellknown equation of Einstein's was off by more than a factor of 10 when applied to this semiconductor material.

“We’re not saying Einstein was wrong, but we have shown that in complicated cases like this, we shouldn’t be using his relation to predict the mobility of excitons from the diffusion,” said team member Matthias Florian.

The team has applied for patent protection and is seeking partners to bring the technology to market.

“The ability to move excitons where we want will help us improve the efficiency of devices that already use excitons and expand excitonics into computing.”

— Parag Deotare

Parag Deotare making adjustments in the lab. Photo: Miranda Howard

Designing Cryogenic Circuits for Quantum Computing

Prof. Dennis Sylvester and doctoral student Qirui Zhang are working with UK company Semiwise Ltd. to develop low-power and cryogenic control electronics, with the ultimate goal of scaling quantum computing for more practical applications.

“We’d like to bring our expertise in lowpower classical computing to a new and exciting domain, namely to efficientl provide control, error correction, and other key functions for emerging quantum computers,” said Sylvester, the Edward S. Davidson Collegiate Professor of Electrical and Computer Engineering.

Quantum computing has the potential to exponentially increase scientists’ ability to model complex simulations, which could revolutionize a myriad of industries including drug development, financial risk profiling, supply chain optimization, and more. However, these promises of quantum computing require significant improvements in the efficiency an reliability of existing technology.

Qubits, the essential units for quantum computing, are typically kept at temperatures near absolute zero, generally around 4 K (-269.15 °C; -452.47 °F). Conversely, the control electronics for the computer operate at room temperature, requiring the cryogenic qubits to be kept at a distance and wired out to the other components of the computer. This arrangement drastically decreases efficien, increases energy consumption, restricts computing power, and limits the practical uses of quantum computers.

Sylvester and Zhang aim to design control electronics that can be used at the frigid temperatures qubits require. However, redesigning the silicon chips and simulating their performance in cryogenic conditions requires substantial time, effort, and funds—prior to building the control electronics.

And that’s where Semiwise can help. The team aims to fast-track the development of cryogenic control electronics using

the company’s proprietary process design kit models.

“Taking standard CMOS down to 4K or -270°C is a major step into new territory where the operating characteristics of the transistors change markedly,” said Prof. Asen Asenov, company founder. “The cryogenic chip design will not only unleash the true power of quantum computers but could also increase significantly the enegy efficiency of th data centers in the transition to a net zero economy.”

“Everything’s new and unknown,” added Zhang. “We are building up the methodology for how to use the superconducting qubits. Our first priority is quality and robustness to maximize the fidelity of contolling that qubit and minimize any potential corruption to the qubit state.”

This new partnership between the University of Michigan and Semiwise makes them a contender in the race to improve the practicality of quantum computing for generalized use.

“We’d like to bring our expertise in low-power classical computing to a new and exciting domain ... emerging quantum computers.”

— Dennis Sylvester

Qirui Zhang working in the lab. Photo: Jero Lopera

iGYM Goes International

The future of recreational play is digitally augmented—and accessible. At least, it can be with iGYM, the spatial augmented reality (AR) system for inclusive play and exercise developed by a team of University of Michigan researchers.

“The creation of iGYM has shown the powerful potential of augmented reality to help people of varying abilities access recreational activities,” said Art and Design Prof. Roland Graf, who co-leads the project with Prof. Hun-Seok Kim.

iGYM uses projected AR to create a room-sized, interactive game environment that was initially modeled after a life-sized version of air hockey. The field, goals, and ball are projections that interact with players, who can pass the ball to their teammates and score goals.

Kim developed the computer vision system that makes the gameplay possible.

“We wanted to make the system more easily deployable for other places, so we separated the computer vision module from the game engine module,” Kim said. “We use a standard ROS2-based distributed service protocol to attach different games developed by different people to the same computer vision engine. So anyone can design a game, and then they simply use our system to demonstrate it.”

In October 2023, the iGYM team partnered with FUTUREGYM, a research group from the University of Tsukuba, who design activities and curriculum that are inclusive for children with both physical and intellectual disabilities.

Here at Michigan, students can take the class “Air Play: Inclusive Augmented Reality Game Development,” which is based on the technology. One of the improvements to iGYM that came out of the course was a change to the user interface design.

“The students made two types of web-based user interfaces: one for the operator and one for the player,” Kim said. “This made it a lot more interactive and fun to use.”

Kim’s team is working to add more features as well, including virtual ultrawideband (UWB) transceivers, and Radio Frequency Identification (RFID) technology.

“There are pros and cons for each type of technology, so we are going to investigate different options to find the one that works best for our system,” Kim said. “It’s a challenging problem, but if we can solve it, we’ll be able to support many new kinds of games as well.”

Other Michigan faculty involved in the project are co-leader Michael Nebeling, School of Information, and Sun Young Park at the Penny W. Stamps School of Art & Design.

“Anyone can design a game, and then they simply use our system to demonstrate it.”

— Hun-Seok Kim

A demonstration of the iGYM/FUTUREGYM collaboration. Photo courtesy of University of Tsukuba.

Teaching Engineers to Protect Public Well-being

As part of her research in Engineering Education, Prof. Cindy Finelli has found concrete evidence that engineering students who receive public welfare responsibility training in classes are more likely to consider the societal impact of technologies they design and to take action when concerns arise after they enter the workforce.

“Results point to a clear need to integrate this kind of training into all facets of higher education for both undergraduate and graduate students,” said Finelli.

This is particularly important because it was found that similar training received elsewhere, such as at work, had comparatively little impact. Yet engineers trained through classes were 30% more likely to have noticed an ethical issue in their workplace and 52% more likely to have taken action about a concerning issue compared to engineers who did not receive training.

In a recent study conducted by Finelli and Sociology Prof. Erin Cech, it was found that only 39% of the engineers surveyed had received public welfare responsibility training in formal engineering classes.

To help with this situation, Finelli and Cech are piloting a one-credit course that will help better prepare engineering students for their public welfare responsibilities. Using data from this study, the professors will prepare case studies for students to dig into and learn how they can intervene when they enter the workforce.

The ultimate goal is to create content that can be integrated into many other engineering courses at the University of Michigan and eventually disseminate teaching materials widely.

“Results point to a clear need to integrate this kind of training into all facets of higher education for both undergraduate and graduate students.”

— Cindy Finelli

While approximately 2/3 of the nation’s engineers do receive this type of training at some point in their career, that still leaves a large number who have never received any training in public welfare responsibilities. Public welfare impact encompasses pressing issues including safety concerns, differential access to the technology, environmental impact or issues of privacy or monitoring.

“My previous work found that ethics instruction compiled into a single course doesn’t have a lasting impact if students see the content as only related to that course. Repetitively reinforcing the importance of ethics and of their responsibilities to the public through instruction is probably the best approach,” said Finelli.

Cindy Finelli teaching a class of undergraduate students. Photo: Robert Coelius

AWARD-WINNING RESEARCH BY STUDENTS

Paper Title: Experimental Investigation of Building HVAC Load-Shifting Efficiency

Conference: 2024 IEEE Power & Energy Society (PES) General Meeting

Authors: Austin Lin, Dr. Shunbo Lei, Prof. Johanna Mathieu (advisor)

Paper Title: In-Situ Calibration of Active Electronically Scanned Antenna Arrays Through SAR Imaging

Conference: 2024 National Radio Science Meeting

Authors: Duncan Madden, Prof. Kamal Sarabandi (advisor)

Quantifying HVAC Load-shifting Efficiency

Austin Lin, ECE doctoral student, received an IEEE PES Prize Conference Paper award for research that aims to optimize the energy use in buildings using their HVAC systems.

“Buildings represent a huge load on the grid,” said Lin, “but it also represents a very flexible load. Unlike when you plug your phone in and you want it to be charging right away, you actually don't really care when the HVAC is turned on, and how much power the HVAC is consuming, as long as the temperature in the building is okay.”

This flexibility in when the power is turned on will help the uility industry better incorporate renewable energy sources into its infrastructure.

To understand more about these dynamics, Lin analyzed an existing dataset of measurements from the HVAC systems of 14 commercial buildings on the U-M campus to quantify their efficien. He was interested in finding out whether soring energy in building “batteries”could be an efficient y to balance and use grid power.

The presented study found that, although the buildings had some ineiencies in returning to their baseline power consumption states after cooling events, the buildings were more effective at shifting their usage on sub-hourly timescales than previous studies had indicated. In addition, the findings indicated that the building thermostats could be tned to improve efficiency an optimize building trade-offs.

Self-calibrating Antennas

Madden Lin, ECE doctoral student, took 2nd prize in the 2024 Ernest K. Smith USNC-URSI student paper competition for research in self-calibrating antennas. This is particularly relevant for antenna arrays that are mounted on aircraft or spacecraft.

“Development of self-calibration methods for antenna arrays would extend the lifetime of arrays deployed for current and future scientific, commecial, or military missions,” said Madden. “It would also reduce maintenance costs and decrease system downtime. Independent calibration is an important step towards automation of the air and space vehicles on which the arrays are deployed.”

Antenna arrays work by adjusting the phase and magnitude of the signal at each antenna element so that the signals constructively or destructively interfere with each other in advantageous ways. If there is some error in how the signals are aligned, system performance can degrade. Calibration is the process of detecting and correcting those errors.

“We addressed the problem by proposing to use backscattered radio frequency signals from the ground below the airborne vehicle as the calibration channel,” explained Madden. “Synthetic aperture radar (SAR) is needed to turn those signals into something usable. From the signals (with SAR), we can form pixelated images, and each pixel can be used as a calibration target. Our experiments so far have shown that this method can be used to accurately determine the channel imbalances between two antennas.”

Paper Title: Simultaneous Transmit-Receive Horn Antenna Based on a Nonreciprocal Metasurface with Embedded Magnetic Bias

Conference: 2024 IEEE International Workshop in Antenna Technology (iWAT)

Authors: Andrew Park, Carl C. Pfeiffer, Andrey A. Chabanov, Prof. Anthony Grbic (advisor)

STAR Antennas

Andrew Park, ECE doctoral student, received a 2024 iWAT Student Paper Award for research on a new simultaneous transmit and receive (STAR) antenna that addresses some of the technical challenges of traditional designs.

STAR antennas can send and receive signals on the same frequency at the same time, allowing for efficient usage of signal bandwidth and fast data ansmission. However, these antennas tend to be large and bulky, due to the ferrite circulators they employ, and often exhibit interference between incoming and outgoing signals.

Park’s new design integrates a horn antenna with a nonreciprocal metasurface that exhibits Faraday rotation.

“Since the circulator design is embedded within the metasurface, the STAR antenna system can be made quite compact by simply attaching the metasurface to an antenna,” explained Park. “This work offers a compelling approach to reducing the overall size of STAR antenna systems.”

This improved STAR antenna, whose development was supported by the Air Force Research Laboratory Sensors Directorate, works at X-band frequencies: a frequency band centered around 10 GHz. STAR antennas in this frequency range can be used for communications or remote sensing.

New Report on Intelligent Vehicle Dependability and Security

Intelligent road vehicles hold great promise for improving the efficiency and sety of our transportation systems, but how safe are they? A group of fie researchers have been working on a report for the past fie years to answer this very question.

The project was initiated in June 2019 by the International Federation for Information Processing (IFIP) Working Group 10.4 on Dependable Computing and Fault Tolerance. Among the team members are Professor Emeritus John Meyer, who helped to establish the group in 1980, and Dr. Carl Landwehr.

Principal findings of the poject point to significant shotfalls in the technologies, cost, governance, and societal aspects of

achieving the end goal of safe and secure self-driving intelligent vehicles, generally referred to as Society of Automotive Engineers Level 4 (full automation, subject to Operational Design Domain [ODD] constraints) or Level 5 (full automation). However, says Landwehr, “Self-driving under highly restrictive ODD constraints— limitations designed to regulate automation based on environmental factors—appears to be a more feasible goal.”

All the project outputs, including the final eport, workshop presentations and video recordings by leading researchers and practitioners in the field, hve been organized into an easily accessible website ivds.dependability.org.

A Coaching Bot to Learn AI

Prof. Raj Rao Nadakuditi is leading the development of a new kind of generative AI coaching bot that is designed to strengthen students’ critical thinking and self-regulated learning skills. His team includes a teenage alum of his online coding class and Prof. David Reeping at the University of Cincinnati (who is also a former U-M postdoc).

“The goal is to develop a bot that will guide students to understand the underlying conceptual framework of a problem in ways that let them self-solve other conceptually similar problems, rather than just tutoring them to solve the specific poblem that had them seek out for help in the first place” Nadakuditi said.

Generative AI refers to a class of algorithms that can be used to generate content, such as text, images, and equations. From opening new possibilities in creative content industries to improving personalized medical plans for patients, generative AI has already made an impact on

society. Many people are already experimenting with how it can be used to enhance learning environments as a personalized tutor for students.

However, by simply providing an answer to the specific quey, a generative AI tutor misses an opportunity to help students build their metacognitive skills. Metacognition is an awareness of how one thinks, which is essential for developing strong critical thinking and problem-solving skills. These skills are particularly important in computational machine learning and AI, as practitioners are expected to leverage algorithms, statistical models, and computational techniques to uncover patterns, identify trends, and automate decision-making processes.

Generative AI tutors could help sharpen students’ metacognition skills by directing students to examine their thinking process. In this way, students can identify how they came to the wrong answer and adjust their process accordingly.

“The goal is to develop a bot that will guide students to understand the underlying conceptual framework of a problem in ways that let them self-solve other conceptually similar problems.”

— Raj Rao Nadakuditi

“This will be one of the first, state of-the-art generative AI applications that explicitly grounds metacognition in a computing education context,” Nadakuditi said. “We want to empower the next generation of scientists and engineers to transform raw domainspecific data ino actionable knowledge, which fuels innovation and drives computationally aided discovery.”

Bringing the JOY OF CODING to Kenya

Fourteen eleventh graders have joined Joy of Coding in Kenya, learning programming skills and teaching them to peers.

When Dale DeJager (BS EE 1973) read about ECE’s online course, Joy of Coding, in a recent edition of Inside ECE magazine, he saw an opportunity to bring this joy to a remote village in Kenya.

Much earlier, in 2009, a newly-retired DeJager had joined the efforts of his friend, Andy Dupont, to build wells for the nomadic Pokot people in Asilong, Kenya. More than a decade later, as the local people began to settle in one area, they saw a need to build the first high school in the area. The school, Asilong Christian High School (ACHS), was completed in 2017.

“The village said, ‘We have no high school. Any students who graduate primary school are having to leave,’” DuPont recalled, “And this is the first generation in the village to be formally educated.”

Today, every student graduating from ACHS qualifies o go on to higher education in Kenya; the typical number in other area schools is about 45%.

In 2019, DeJager and DuPont built a solar-powered computer lab for the school, and DeJager used his wireless expertise to set up internet access. They then helped locate a talented local teacher for the class, Juliet Rabach.

Dale DeJager teaches a computer class at Asilong Christian High School in Kenya. Photo: Andy DuPont

“When I came to know about the Joy of Coding, I gained a lot of interest because coding is really part of IT,” Rabach said, “Without coding, there are so many things that you can’t understand.”

Together, Rabach, DeJager, and DuPont selected a pilot cohort of fie outstanding students to take the class in 2023.

Joy of Coding was a hit with the students, who worked hard to complete the coursework even with the unforeseen challenges of running a course in a new location.

“I learned many, many things that I didn’t know,” said one of the students, Paul Lokapel. “The class also helped me to make my other classes easy and—even if I wasn’t doing computer classes—I could apply the learnings to my normal life.”

But, he said, “There were some struggles that made it a difficult class.or instance, when we go home for holidays, there’s no computer, phone, or email, so that interrupts the class.”

Despite these and other challenges, the students overwhelmingly echoed Lokapel’s positive feedback about the course. “When working on the Joy of Coding, we learned something that is helpful to our lives, and also we enjoyed it,” said Dorcas Chebet.

“This course enables someone to think critically,” noted Emmanuel Akori, “And your career may depend on the certificates that ou get from the courses that you’ve taken.”

In Kenya, students must declare a specialty during the national examination that determines whether they will qualify for college or university. Many of the students emphasized that they would continue taking computer classes and pursue a career in computing—following in Rabach’s footsteps.

This the first time Jy of Coding reached an organized international cohort, and the course’s developer, Prof. Raj Rao Nadakuditi, was delighted with the results.

“Running Joy of Coding in Asilong gave me a sense that the format could work everywhere and that increasing access and explicitly teaching selfdirected learning skills are the key to realizing the (as yet, unfulfilled) deam of having way more people, in every part of the country and the world, do and learn way more,” said Nadakuditi.

In the meantime, student interest in the course continues to grow. “Maybe we’ll have more next year—we have computer facilities that could easily handle 20 students,” said DeJager.

The homestead of a typical student attending Asilong Christian High School.

Dale DeJager outside the school.

The first cohort of Joy of Coding students in Asilong, Kenya, with Dale DeJager (L) and teacher Juliet Rabach (R).

New Books

2D Excitonic Materials and Devices

Parag B. Deotare and Zetian Mi, Editors

2D Excitonic Materials and Devices is Vol. 112 in the Semiconductors and Semimetals series published by Elsevier. Co-edited by Professors Parag Deotare and Zetian Mi, the book covers the most exciting developments in two-dimensional excitonic materials, with a focus on applying the physics that has been developed since the discovery of graphene in 2004.

Using 2D excitonic materials to design devices has the potential to revolutionize applications such as mid-infrared spectroscopy, UV LEDs, next-generation lasers, on-chip data communication and processing, and many more. These applications have been left unexplored because of the lack of a material system that could support a mobile exciton at room temperature, as well as the primary focus of researchers on studying and advancing the governing physics of 2D excitonic materials.

Linear Algebra for Data Science, Machine Learning, and Signal Processings

Jeffrey A. Fessler and Raj Rao Nadakuditi

This new textbook by Professors Jeffrey Fessler and Raj Nadakuditi is designed to be used in a graduate-level course that they have taught in the department for the past ten years, Matrix Methods for Signal Processing, Data Analysis and Machine Learning.

“The goal of this class, and therefore the book, is to make sure that students can read the current literature on matrix-based methods for signal processing, machine learning, and data

science,” explained Fessler, the William L. Root Distinguished University Professor of EECS. “It’s a big leap between what they’ve learned as an undergrad and that literature, so there has been a need for a book to help students with that bridge.”

Traditionally, ECE students have taken linear algebra courses in the math department or learned from math textbooks, where they solve equations but may learn less about their applications.

“I thought it was appropriate to introduce the theory alongside the application, rather than the traditional format— which is to first do all the theoy and then the applications," said Nadakuditi."

Emerging Ferroelectric Materials and Devices

John Heron and Zetian Mi, Editors

Emerging Ferroelectric Materials and Devices, Vol. 114 in the Semiconductors and Semimetals series, is co-edited by Prof. Zetian Mi and Prof. John Heron (Materials Science and Engineering Department).

“Many of us, before we were even born, have dealt with ferroelectricity because it is used very commonly in ultrasonics,” said Mi. “It has been known for over 100 years and, in the last several decades, has drawn lots of attention because this material has so many applications. For example, it has been widely used for energy storage in supercapacitors because of the very large dielectric constant. More recently, an exciting development is microelectronics in memory applications.”

The book covers the latest developments in traditional oxide ferroelectrics, as well as in emerging nitride ferroelectrics, which are well-suited for use in microelectronics due to their potentially high endurance, small size, and low power consumption. This next generation of ferroelectrics could be a game-changer for non-volatile memory, which allows the storage of information in the absence of constant electric power.

21st William Gould Dow Distinguished Lectureship

This lectureship is the highest honor bestowed on a guest speaker by the Department, and honors William Gould Dow (1895–1999), former faculty member, Department Chair, and pioneer in electrical engineering education.

Andrea Goldsmith, Dean of Engineering and Applied Science and Arthur LeGrand Doty Professor of Electrical and Computer Engineering at Princeton University, presented the 21st William Gould Dow Distinguished Lecture to a packed room, interested to hear her talk on “Disrupting Next G.”

Her talk was both personal and technical, following her 40-year career in wireless technology—a career that earned her membership in the National Academy of Engineering, the Royal Academy of Engineering, and the American Academy of Arts and Sciences.

Goldsmith spent her career as an academic, teaching at CalTech and Stanford before being called to Princeton. But she also found time to start the company Quantenna in 2005, which developed the best WiFi chip in the world at the time. She founded her second company, Plume WiFi, in 2010; this company designed cloud software to manage wireless networks. She said the startup work was “exciting and challenging and terrifying and awful.”

Goldsmith received several awards for this innovative work, including induction into the National Inventors Hall of Fame, the ACM Sigmobile Outstanding Contribution Award, the IEEE Sumner Technical Field Award, and the ComSoc Armstrong Technical Achievement Award. She is the first woman to receive the Marconi Prize, and she has been inducted into the Silicon Valley Hall of Fame.

“If you found a startup to make money, you are unlikely to be successful because most startups fail. If you start

a company to see if your research matters in practice, you will likely be very rewarded,” said Goldsmith.

As Goldsmith’s leadership and seniority within the field has gown, she has been more intentional about the ways that she promotes diversity, equity, and inclusion in the profession. She founded and chaired the IEEE Board of Directors Committee on Diversity, Inclusion, and Equity.

Her work as an inclusive educator and mentor has been recognized with the ACM Athena Lecturer Award and several IEEE honors, including the Education Medal, the Kirchmayer Graduate Teaching Award, and the WICE Mentoring Award. She is author of the book Wireless Communications, and co-author of two other books.

“If you start a company to see if your research matters in practice, you will likely be very rewarded.”

— Andrea Goldsmith

Goldsmith’s current work focuses on methods to improve the next generation of wireless technologies and to use them for compelling applications. She envisions the future of wireless technology to be energy efficient, sece, reliable, and fast—capabilities that must be developed to support a host of new applications that will change people’s lives for the better.

Watch Goldsmith’s talk

Andrea Goldsmith is presented with the William Gould Dow Distinguished Lectureship Award by former Interim Chair Dennis Sylvester (L) and Prof. Vijay Subramanian (R). Photo: Mena Davidson

ECE Expeditions heads back to Silicon Valley

Since the first ECE Expeditions outing in 2016, ECE undergraduate and graduate students have been exploring tech companies both locally and throughout the U.S. From startups to international tech powerhouses, these companies have welcomed our students and given them the rare opportunity to network with potential employers while giving them an insight into the life of an industry-bound electrical and computer engineer.

The most recent trip brought them back to Silicon Valley to visit Meta, Kodiak Robotics, KLA, and SiTime.

“By participating in this trip, I enhanced my understanding of diverse engineering applications, gained valuable insights from experienced professionals, and expanded my ECE network,” said ShihChi Liao, ECE PhD student.

“You get the experience to speak to engineers in the field and learn about the endless paths that an ECE degree can take you. For anyone on the fence whether they want to go on this trip, I think it is 100% worth it,” said Sophie Millhouse, ECE undergraduate student.

 Meta is commonly recognized as the parent company of popular apps including Facebook and Instagram. Their newest projects focus on generative artificial intelligence and vitual reality.

 SiTime develops the silicon MEMS semiconductors used for precision timing, which allows electronic devices to synchronize with each other and keep time accurately.

The Expeditions were the brainchild of the first ECE Council. Thank you Council members!

 KLA develops equipment and supplies essential for high tech applications, including computers, autonomous vehicles, space exploration, virtual reality, artificial intelligence, and more.

 Kodiak Robotics is a startup company driven to increase road safety and shipping efficiency tough its state-of-the-art integration of sensors and artificial intelligence

Expedition students visit Meta.

Photo: Silvia Cardarelli

Expedition students visit SI Time.

Photo: Silvia Cardarelli

Expedition students visit the KLA Cleanroom.

Photo: Silvia Cardarelli

Expedition students visit Kodiak Robotics.

Photo: Silvia Cardarelli

EDUCATION NEWS

“MY FAVORITE PART ABOUT CAMP WAS GOING ON CAMPUS TOURS WITH OTHER STUDENTS AND THE Q&A SESSION. I MET MANY STUDENTS AND CAMPERS AND EVEN MADE NEW FRIENDS (EVEN A GROUP CHAT)!” —STUDENT CAMPER

ECE’s flagship tech camp, Electrify, expanded this year to include 5 different camps. These five-day, non-residential camps are open to high school students who are eager to experience a fun introduction to electrical and computer engineering. They are taught by ECE faculty and students, include lab and team-building activities, and give students a feel for life at Michigan.

Photos: Jero Lopera

NANOCAMP

The world of “small” with a hands-on intro to semiconductor chip design, and solar-powered cars

“I LEARNED ABOUT HOW LASERS WORK AND DIFFERENT SCIENTIFIC PRINCIPLES LIKE STIMULATED EMISSION AND REFRACTION.”

—STUDENT CAMPER

“I LEARNED SO MUCH MORE ABOUT AI THAN I HAD KNOWN BEFORE. I HAD ALWAYS WONDERED HOW THE MAGIC OF IT WORKED, BUT THIS WEEK WAS A REALLY GREAT WINDOW INTO THE DETAILS AND THE ENGINEERING BEHIND IT.”

—STUDENT CAMPER

“[I LEARNED] PROBLEM SOLVING WITH THE SOLAR CAR, AS WELL AS EVERYTHING WE DID IN THE CLEAN ROOM, WHICH WAS A SUPER FUN EXPERIENCE.”

—STUDENT CAMPER

ENTANGLE IT

The strange and eerie world of quantum

ZAP IT

Light, lasers, and plasma

AIMAGIC

You guessed itartificial intelligence!

POWERUP

Power, energy, and electric vehicles

“SOLDERING, CAR RACE, TOURS, AND LECTURES WERE AWESOME!”

—STUDENT CAMPER

Family Fun Night Shares the Wonders of ECE with the Community

About every two years, faculty, students, and especially staff work together to offer a super fun event that is open to the community. This past year, more than 300 people attended ECE Family Fun Night on September 29, 2023.

Those who came were exposed to a variety of interactive demos that gave a glimpse into the wondrous world of electrical and computer engineering. The demos included the topics of robotics, holography, lasers, wireless power transfer, portable analog kits, imaging, organic semiconductors for solar energy and LEDs, and info about the Lurie Nanofabrication Facility. Student teams including Supermileage, MRover, and MASA brought their projects for people to explore and study, and Baja Racing presented one of their previous cars.

Attendees also enjoyed engineering-inspired craft areas, tasty food, and a variety of carnival attractions that included a bouncy house, a photo booth, face painting, and a dunk tank (where professors got all wet).

Photos: Miranda Howard

WELCOME to our New Faculty

Five new faculty will be continuing their academic careers at Michigan beginning Fall term 2024 or later, bringing their expertise in the areas of computer vision, cyber-physical systems, machine learning and AI, energy storage, HCI, and personalized medical devices.

INIGO INCER

Assistant Professor

Research Interests: Compositional system design, design automation, formal methods, control systems, computational logic, AI, cyber-physical systems.

Inigo Incer was most recently a postdoctoral researcher at Caltech. He received his PhD in Electrical Engineering and Computer Sciences from UC Berkeley. Incer’s group develops theory, software, and engineering methodologies to support complex systems design. They work closely with experts across various domains—such as aerospace, autonomy, synthetic biology, and transportation—to apply and extend the capabilities of these system-design techniques. Incer joined Michigan September 2024.

JUN GAO

Assistant Professor

Research Interests: Computer vision, computer graphics, and generative AI.

SHUBHANSHU SHEKHAR

Assistant Professor

Research Interests: Machine learning, statistics.

Jun Gao is currently a PhD student at the University of Toronto, and a research scientist at NVIDIA. He is interested in developing 3D generative AI models to create realistic, high-quality and diverse 3D content for reconstructing, generating and simulating lifelike 3D worlds, catalyzing applications across VR/AR, robotics, autonomous vehicles and more broadly the metaverse. Gao will join Michigan September 2025.

Shubhanshu Shekhar was most recently a postdoctoral researcher at Carnegie Mellon University. He received his PhD in Electrical Engineering from UC San Diego. He is particularly interested in developing sequential and adaptive decisionmaking methods that remain valid under minimal model assumptions. He has worked on nonparametric hypothesis testing, estimation, change detection, active learning, Bayesian optimization, and adaptive resource allocation. Shekhar joined Michigan September 2024.

New Fellows

ZIYOU SONG

Assistant Professor

Research Interests: Modeling, estimation, optimization, and control of energy storage.

Ziyou Song was most recently an Assistant Professor at the National University of Singapore. Prior to this position, he worked at Apple as a Battery Algorithm Engineer, and as an Assistant Research Scientist in ECE. He received his PhD at Tsinghua University. Using energy storage as a bridge, his research group connects automotive, transportation, and power system communities through interdisciplinary projects. He is committed to developing efficient,eliable, and clean power and transportation systems. Song will join Michigan January 2025.

JUNYI ZHU

Assistant Professor

Research Interests: Intersection of Human Computer Interaction, fabrication and novel sensing technologies.

Junyi Zhu recently graduated from MIT EECS Department and Computer Science and Artificial Intelligence Laboatory (CSAIL). He works at the intersection of novel sensing technologies, fabrication and human-computer interaction, with an emphasis on health and medical applications. He designs and fabricates personalized health and medical sensing devices for both in-field and in-clinic envionments to provide more temporal and spatial information for physicians. Zhu will join Michigan January 2025.

P.C. KU

Fellow of Optica

Ku’s research on nanostructured optoelectronic materials and devices has led to major technological breakthroughs, most notably in semiconductor light-emitting diodes (LEDs) and slow light devices, with applications ranging from quantum photonics to sensing, and from fundamental device physics to LED luminaire design.

“For pioneering contributions to semiconductor nanostructured optoelectronic materials, devices, and their applications.”

DI LIANG

IEEE Fellow

At Hewlett Packard Labs, Liang led silicon and III-V integrated photonics research, which included the innovation of a new III-V quantum-dot-onsilicon heterogeneous photonic integration platform for high-performance interconnect and computing. He also invented a heterogeneous MOSCAP structure with phase tuning that was >1,000,000,000x more energy efficient than coentional thermal tuning.

“For contributions to photonic integration in optical communication, computing, and volume production.”

FACULTY AWARDS

JEFFREY FESSLER

Named Interim Chair of Electrical and Computer Engineering

Named William L. Root Distinguished University Professor of EECS

Jeffrey Fessler was named Interim Chair of Electrical and Computer Engineering, effective July 1, 2024, and was also recently appointed as the William L. Root Distinguished University Professor of Electrical Engineering and Computer Science.

Prof. Fessler and his group have had a far-reaching impact on the medical image reconstruction field y combining advanced methods from signal processing with accurate physical and statistical models for these imaging systems. He has advanced the fields of Magnetic Resonance Imaging (MRI), -ray Computed Tomography (X-ray CT), and radionuclide imaging (PET/SPECT) by making these technologies faster, safer and more cost effective, without sacrificing image qualit.

His research has been used to reduce X-ray dose in CT systems made by General Electric and introduced at the University of Michigan hospital in 2012. His method for improving SPECT imaging used in cardiac stress tests in the late 1990’s was subsequently used by thousands of patients at U-M hospital. And his technique to speed up the time needed to generate a CT scan, which is done about 80 million times per year in the U.S. alone, has made these scans safer for all patients.

Fessler currently has 13 U.S. patents, but that doesn’t tell the whole story, as he is also a pioneer and strong advocate for open research. For example, his Michigan Image Reconstruction Toolbox (MIRT) is a collection of open source algorithms for image reconstruction and related imaging problems. MIRT has been downloaded thousands of times.

His previous honors and awards include the IEEE EMBS Technical Achievement Award, Edward J. Hoffman Medical Imaging Scientist Award, U-M Distinguished Faculty Award, and U-M Distinguished Graduate Mentor award. He also received the HKN Professor of the Year award three times. He recently co-authored the textbook Linear Algebra for Data Science, Machine Learning, and Signal Processing, and he is an IEEE Fellow. Fessler has courtesy appointments in Biomedical Engineering and Radiology.

Chen-Luan Family Faculty Development Professorship

Necmiye Ozay is the inaugural recipient of the Chen-Luan Family Faculty Development Professorship. Ozay is a leading expert in hybrid systems and system identification. Her research interests include dynamical systems, control, optimization, and formal methods with applications in cyber-physical systems, system identification, verification and alidation, and autonomy. She has already made fundamental contributions that have had far reaching impacts on control theory, as well as related fields, such as computer vision, machine learning, and formal erification

An early proponent of correct-by-construction control of hybrid systems, Necmiye’s research has resulted in these systems being more robust and safer. She has applied her expertise to real-life systems in collaborations with numerous industrial partners, including United Technologies Aerospace Systems, Toyota Research Institute, and the Ford Motor Company. Her awards include an NSF CAREER Award, a DARPA Young Faculty Award and Director’s Fellowship, an ONR Young Investigator Award, and a NASA Early Career Award.

NECMIYE OZAY

Radar technology trailblazer Kamal Sarabandi received the Ellis Island Medal of Honor. This award recognizes individuals for excellence and service to the country in professional, cultural and civic roles. Those honored embody “the spirit of inclusivity and resilience that has defined America thoughout its history,” according to the nonprofit Ellis Island Honors Societ.

Recipients include leaders from across society—politics and civil rights, entertainment and the arts, business, military, science, technology and medicine. Past honorees include six U.S. presidents, CEOs of Fortune 500 companies, Nobel laureates, and cultural figues. Sarabandi and the other recipients were awarded the medal May 18, 2024 on Ellis Island in New York City.

Sarabandi was described in the award materials as “a legendary figue in the field of electrical engineering.” He is a member of the National Academy of Engineering and a fellow in the American Association for the Advancement of Science. At Michigan, he is the Fawwaz T. Ulaby Distinguished University Professor and Rufus S. Teesdale Professor of Engineering. He is also an ECE alumnus.

Sarabandi’s philosophy has always been that research should matter outside of scientific journals. He turned the adar discoveries he made during his PhD studies into systems that can monitor key climate change indicators from space, specifically soil moistue and the carbon stored in plants. From there, he went on to lead a $20-million center, funded by the Army Research Lab, that developed a suite of robots with compact, lightweight radar systems that collaborate to see through rain, smoke and even walls. More recently, his team has turned to developing radar for autonomous vehicles in order to detect obstacles in all kinds of weather.

Samuel H. Fuller Early Career Professor of Electrical and Computer Engineering

Hun-Seok Kim was named the inaugural Samuel H. Fuller Early Career Professor of ECE. Kim’s work has consistently improved the efficien, size, and communication functions of sensing devices. One of his early contributions was an efficient an flexible system-on-chip called ASH-SoC, designed to improve intelligent wireless communications for applications including cellular networks and inter-satellite space links. His research group also developed an ultra-energy-efficient ocessor that allows a small autonomous drone to compute its location and orientation while mapping its surroundings.

Kim is currently using tiny sensing computers known as Michigan Micro Motes to track the migration of monarch butterflies, in collaboation with conservation biologists. He also co-developed iGYM, an augmented reality platform that allows disabled children to play a physical sport equitably with non-disabled children. Kim has received a DARPA Young Faculty Award, an NSF Career award, and fie best paper awards for his research. He holds 22 U.S. patents.

Ellis Island Medal of Honor

KAMAL SARABANDI

HUN-SEOK KIM

FACULTY AWARDS

Cindy Finelli, the newly-appointed David C. Munson, Jr. Collegiate Professor of Engineering, is a trailblazer and leader in the area of Engineering Education Research (EER). She was the first faculty member hied under the College of Engineering’s EER initiative in 2015, and three years later became inaugural director of the EER graduate program.

Her research is focused on teaching and learning at the undergraduate level, and on faculty professional development. A strong proponent of active learning, she identified stategies instructors can use in the classroom to lower student resistance to active learning, and she continues to advocate for faculty adoption of evidence-based teaching practices.

Finelli’s recent research includes goals of enhancing the success of college students with ADHD, and improving an engineering student’s understanding of the sociotechnical impact of technology. She is also a strong advocate for DEI in engineering, and helped establish a virtual seminar series to bring top scholars to U-M to present on research about the experiences of students who are BIPoC (Black, Indigenous, People of Color) in engineering.

Finelli is a Fellow of IEEE and the American Society of Engineering Education. She has received several best paper awards and numerous professional honors and awards, including a Premier Award for Engineering Education Courseware. She has served as Deputy Editor for Journal of Engineering Education.

Anthony Grbic, the newly-appointed John L. Tishman Professor of Engineering, is a world leader in the development of metamaterials and metasurfaces, which are engineered materials and surfaces whose fine textues dictate their unusual electromagnetic properties. His pioneering research has led to ultra-thin electromagnetic and optical devices with unprecedented capabilities, and to the development of new opportunities in low-profile antennas, lenses and ultrathin 3D holographic platforms. His work has been foundational for achieving unusual phenomena such as near-field, lens-fee focusing, understanding electromagnetic structures whose properties vary in both space and time, and more.

Recently, Grbic has been developing time-varying metamaterials whose properties can vary both in space and time, resulting in more efficient and cost-eective ways to transmit and receive electromagnetic waves. The work has applications in next-generation wireless communication, commercial and military radar systems, imaging, and antenna systems.

Grbic has received the U-M Henry Russel Award, David E. Liddle Research Excellence Award, U-M Faculty Recognition Award, and the Ernest and Bettine Kuh Distinguished Faculty Award. He has also earned the MTT-S Outstanding Young Engineer Award, USNC/URSI Booker Fellowship, AFOSR Young Investigator Award, NSF CAREER Award, and Presidential Early Career Award for Scientists and Engineers. He is an MTT-S Distinguished Microwave Lecturer, and IEEE Fellow.

Cindy Finelli and David C. Munson, Jr.

John L. Tishman Professor of Engineering

ANTHONY GRBIC

David C. Munson, Jr. Collegiate Professor of Engineering

CINDY FINELLI

Anthony Grbic (seated), with (L) Kamal Sarabandi, former Dean Steven Ceccio, Eric Michielssen, former Interim Chair Dennis Sylvester

FACULTY AWARDS

James

R. Mellor Professor of Engineering

Wei Lu, the newly-appointed James R. Mellor Professor of Engineering, is an internationally recognized leader in the development of memristors for memory and logic applications. Lu’s group developed many of the first concepts elated to memory systems, in-memory computing architectures, and neuromorphic computing architectures. He has also developed nanowire transistors suitable for flexible electonics and optoelectronics, and he conducts research regarding other emerging electrical devices.

Lu’s more recent research has demonstrated efficient image analysis using hi novel circuits, as well as methods to perform general, data-intensive computing based on this new hardware system. This work is applicable to fields such as pervasive sensing, Internet of Things, autonomous vehicles and other Big Data tasks, and has attracted interest from conventional semiconductor companies, oil and gas companies, and defense contractors. He founded the companies CrossBar, Inc. and MemryX, Inc. based on his research. CrossBar offers a unique memory technology called Resistive RAM, or ReRAM. MemryX is a fabless semiconductor chip company developing an Edge AI accelerator.

Lu has received the Distinguished University Innovator Award, the Ted Kennedy Family Faculty Team Excellence Award, the David E. Liddle Research Excellence Award, the Rexford E. Hall Innovation Excellence Award, and an NSF CAREER award. He is an IEEE Fellow.

Robert J. Hiller Professor of Engineering

Leung Tsang, the newly-appointed Robert J. Hiller Professor of Engineering, is a world-renowned expert in the field of theoetical and computational electromagnetics, and in particular microwave remote sensing of the earth. His research interests include: remote sensing; multiple scattering of waves, wave propagation in random media and rough surfaces; electromagnetic theory; photonic crystals and plasmonics; as well as signal integrity and electromagnetic compatibility.

Tsang played a major role developing theoretical models that have been the bases of microwave sensors mounted on satellite missions for continual global monitoring. The measurements taken through his methods have contributed to a clearer picture of the global climate and the effects of warming. Tsang shares several of his computer codes and simulations on his website. Among these are lookup tables for sea ice surface for both active and passive observations, rough soil surface scattering and emission, and a toolkit to model the microwave signature of multi-layered snowpacks.

Tsang has received numerous awards, including the IEEE Electromagnetics Award, the William T. Pecora Award, the Golden Florin Award, the Van de Hulst Light-Scattering Award, IEEE GRSS Distinguished Achievement and Outstanding Service Awards, and the IEEE Third Millennium Medal. He is a Fellow of IEEE, the Optical Society of America, and the Electromagnetics Academy. Tsang is a member of the National Academy of Engineering.

WEI LU

LEUNG TSANG

Wei Lu (seated), with (L) former Dean Steven Ceccio, former Interim Chair Dennis Sylvester, Jay Guo

Dean Karen Thole, Leung Tsang, Interim Chair Jeff Fessler, Kamal Sarabandi

5th Annual Juneteenth Celebration Hits a High Note

JUNETEENTH

Celebration 2024

On June 19, 2024, the University of Michigan Electrical Engineering and Computer Science (EECS) Department held its fifth annual—and first in-person—Juneteent celebration. Over 200 enthusiastic community members braved the heat to celebrate the historic holiday that commemorates the end of chattel slavery in the United States.

The celebration was spearheaded and emceed by Herbert Winful, University Diversity and Social Transformation Professor, Arthur F. Thurnau Professor, and Joseph E. and Anne P. Rowe Professor of Electrical Engineering at U-M.

“Today, let us all recommit to the principles at the center of Juneteenth: freedom, justice, and equality for all.” — Lt. Gov. Garlin Gilchrist II

The event featured talks by distinguished alumni Shawn Blanton (PhD CSE 1995), the Joseph F. and Nancy Keithley Professor of Electrical and Computer Engineering at Carnegie Mellon University, and James Mickens (PhD CSE 2008), the Gordon McKay Professor of Computer Science at Harvard University.

Attendees also enjoyed presentations by students and two musical performances. It was topped off with a free lunch for attendees who braved the heat and humidity to enjoy the cuisine of two Black-owned food trucks, Good Eats and Motor City Sweet Treats.

Watch the program

Program Highlights

Recorded remarks by EECS alum and Michigan Lt. Gov. Garlin Gilchrist II

Performance of Lift Every Voice and Sing by music student Amber Rogers, accompanied by Herbert Winful, Joseph E. and Anne P. Rowe Professor of EE

Emancipation Proclamation and additional remarks, by U-M graduate students

“EASE: Empowering Access for Social Equity,” by Shawn Blanton, Joseph F. and Nancy Keithley Professor of ECE, CMU

"Computers: Deep Ethical Dilemmas and Other Breezy Conversational Topics,” by James Mickens, Gordon McKay Professor of CS, Harvard

Remarks by incoming Chair of CSE, Atul Prakash, and incoming Interim Chair of ECE, Jeffrey Fessler

Performance of “In-Visibility,” composed by Emmy Award Winner Jasmine Arielle Barnes, by Prof. Tiffany Ng, carillonist and Organ Department Chair

Amber Rogers sings “Lift Every Voice and Sing,” accompanied by Prof. Herbert Winful. Photo: Emily France

Professor Pallab Bhattacharya joined the department January 1, 1984, after having been on the faculty at Oregon State University since 1978. He hit the ground running, and has scarcely taken time to catch his breath in the past 40 years. After officiallyetiring January 1, 2024, Bhattacharya will continue to work on a few research projects.

After coming to Michigan, Bhattacharya initiated research and teaching in optoelectronics. He established extensive experimental facilities, including those for semiconductor epitaxy with a technique known as molecular beam epitaxy (MBE). These MBE facilities were the first of their kind at Michigan

He has been a renowned leader in the development and commercialization of quantum dot lasers and devices for a wide range of applications. This was precipitated by his group’s discovery of the self-organized formation of quantum dots in strained channel heterostructure transistors in 1988, and the subsequent demonstration of room temperature operation of a quantum dot laser.

Bhattacharya and his group demonstrated the first semiconducor based spin valve, spin amplifie, and an electrically injected spin laser and spin polariton laser. His group was also the first o report quantum dot lasers

PALLAB BHATTACHARYA

Retires, Leaving a Rich Legacy of Optoelectronics Research andTeaching

emitting in the entire visible wavelength range, with III-nitride heterostructures.

A prolific esearcher, Bhattacharya has disseminated his group’s research results in over 1,000 archival journal articles and plenary, invited and contributed conference presentations, and authored three U.S. patents.

He graduated 81 Ph.D. students, many of whom are leaders in industry and academia around the world; they are even represented in the United Nations. One of his most often-repeated comments both publicly and privately has been, “I have been blessed throughout my career to have the most dedicated doctoral students to work with me.”

Bhattacharya introduced four undergraduate and graduate courses in the area of semiconductor devices, lasers and light emitting diodes. He authored the influential textbook Semiconductor Optoelectronic Devices, which is now in its second edition and has been used worldwide for over 30 years. He has edited and co-authored the widely used Properties of Lattice Matched and

Strained InGaAs and Properties of III-V Quantum Wells and Superlattices. He is also co-Editor-in-Chief and co-author of the six-volume Comprehensive Semiconductor Science and Technology.

Among his many honors are an Honorary Doctorate from the University of Sheffield, UK, and a John Simo Guggenheim Fellowship. He received the IEEE Jun-ichi Nishizawa Medal, the Molecular Beam Epitaxy Innovator Award, the IEEE David Sarnoff Award, the Heinrich Welker Medal, the TMS John Bardeen Award, the IEEE Nanotechnology Pioneer Award, the Optica Nick Holonyak Jr. Award, the IEEE (LEOS) Engineering Achievement Award, a SPIE Technology Achievement Award, and an IEEE EDS Paul Rappaport Award.

He is a Fellow of IEEE, the American Physical Society, Optica, the Institute of Physics (UK), and the National Academy of Inventors. He was elected a member of the National Academy of Engineering, “For contributions to quantum dot optoelectronic devices and integrated optoelectronics.”

Attendees of the Frontiers in Semiconductor Based Devices Symposium, held in honor of Pallab Bhattacharya’s 60th birthday.

Professor Meerkov received an M.S.E.E. (1962) from the Polytechnic of Kharkov in Ukraine and a Ph.D. (1966) from the Institute of Control Sciences in Moscow, Russia. He served as Automation Engineer (1962-63) at the Research Institute for Power Systems Automation in Kharkov, Ukraine and as Research Fellow (1966-69) and Senior Research Fellow (1969-77) at the Institute of Control Sciences in Moscow, Russia. He joined the Illinois Institute of Technology in the Electrical Engineering Department as Associate Professor in 1979, and was promoted to Professor in 1982. He joined the University of Michigan as Professor in 1984.

Professor Meerkov’s research focused on systems and control, production systems engineering, communication networks, rational behavior, and resilient control systems.

During his time at Michigan, he taught undergraduate courses on signals and systems, probability theory, and feedback control and graduate courses on nonlinear systems, nonlinear control, and new courses on Production Systems Engineering.

SEMYON MEERKOV

Retires, and Continues his Work on Production Systems Engineering

Meerkov co-authored the first textbook in the field of poduction systems titled Production Systems Engineering. This book is used in many countries throughout the world and received the Excellent Textbook Award for its 2012 Chinese translation. He also co-authored the book Quasilinear Control, which serves as the text for the graduate course Advanced Nonlinear Control. He published nearly 300 refereed journal publications and conference papers, seven of which earned best paper awards.

A devoted educator, Professor Meerkov was voted Eta Kappa Nu Professor of the Year in 1997 by the students themselves. He graduated 31 Ph.D. students, many of whom are distinguished professors around the world or leaders in industry.

As a member of the University of Michigan’s Faculty Senate, Professor Meerkov served in the Senate Assembly and on the Senate Advisory Committee on University Affairs, helping to

establish annual faculty evaluations of administrators, unit-shared governance in the College of Engineering, and university-wide shared governance. He was instrumental in creating a faculty fund for need-based scholarships. For his efforts, he received U-M’s Distinguished Faculty Governance Award (2008).

The production systems engineering methods developed in his research group have been applied to dozens of production systems in large, mid-size, and small manufacturing organizations. He is co-founder and President of Smart Production Systems LLC. He is a Life Fellow of IEEE and a Foreign Member of the Russian Academy of Sciences.

On November 3, 2023, shortly before retiring, Meerkov was the speaker at the weekly Control Seminar Series (which he helped to establish in 1985). He offered the talk, “Research problems of my life: Overview and advice for the inspired.”

Semyon Meerkov presents his retirement talk to a packed room at the Control Seminar Series.

Prof. Wayne Stark began his career at Michigan as an assistant professor the same year he received his doctoral degree, 1982. He retired December 31, 2023, after 41 years advancing the field of wireless communications and educating countless undergraduate and graduate students.

Stark’s research was focused on digital communication theory and practice, with particular emphasis on wireless communications, spread-spectrum communications, and error control coding theory. He had strong industrial ties, spending sabbatical years at IBM, Ericsson, and Microsoft, and consulting for various companies including Ericsson and Uhnder, which was co-founded by former student Manju Hegde.

Stark published more than 200 refereed journal articles and conference proceedings, authored 6 book chapters, authored more than a dozen U.S. patents, and one textbook. He graduated 39 PhD students.

He taught undergraduate and graduate courses in the areas of probability, analog communications, signal and

WAYNE STARK Retires after 41 Years Advancing the Field of Wireless Communications

systems, digital communications, information theory, communication networks, software-defined adio, and channel coding theory. He also taught a University of Michigan summer short course on spread-spectrum communications and its applications (1993-96), and introduced and taught a wireless communication camp for high school students (2010-2011).

In the Department of Electrical Engineering and Computer Science, he served as Associate Chair for the former division of Electrical Engineering: Systems (1997-2000), and as area director for networking, communications and information systems (2015-2022). He served on the Senate Advisory Committee on University Affairs (20072010), the Rules Committee (2014-17), the Scholastic Standing Committee (2021-22) and the International Programs in Engineering Advisory Committee (2021-22).

Stark was Associate Editor of IEEE Transactions on Communications and

guest editor for numerous special issues for the IEEE Journal on Selected Topics in Communications on wireless communications and wideband code division multiple access (WCDMA). He was a member of the Board of Governors of the IEEE Information Theory Society (1985-88). He also co-organized the 1986 IEEE International Symposium on Information Theory, held in Ann Arbor, MI.

In 2021, Stark was honored at the event, Wireless Communications: A Symposium Honoring Prof. Wayne Stark. Several of his former students and colleagues gave talks.

He received an NSF Presidential Young Investigator Award (1985), the IEEE MILCOM Board Technical Achievement Award (2002), and the IEEE Military Communications Conference Ellersick Best Paper Award (2009). He is an IEEE Fellow, “For contributions to the theory and practice of coding and modulation in spread-spectrum systems.”

Students in the summer tech camp created by Wayne Stark in 2010.

Additional Faculty Honors and Awards

PALLAB BHATTACHARYA

Charles M. Vest

Distinguished University

Professor Emeritus of EECS

Al Cho MBE Award

ZETIAN MI

Professor

EECS Outstanding Achievement Award

CoE Rexford E. Hall Innovation Excellence Award

2024 ISCS Quantum Devices Award

KAMAL SARABANDI

Fawwaz T. Ulaby

Distinguished

University Professor of EECS

IEEE AP-S Legend of Electromagnetics, Inaugural Member

MACK KIRA Professor

CoE Monroe-Brown Foundation Service Excellence Award

STÉPHANE LAFORTUNE

N. Harris McClamroch Professor of EECS

2024 HKN Professor of the Year

RAJ RAO

NADAKUDITIU

Associate Professor

U-M Master’s Mentoring Award

JOHN NEES

Research Scientist

U-M Research Faculty Achievement Award

WEI LU

James R. Mellor

Professor of Engineering

Editor-in-Chief of npj: Unconventional

Computing, new openaccess Nature journal

ANDREW OWENS

Associate Professor

CoE 1938E Award

JOHANNA MATHIEU

Associate Professor

Director, Institute for Energy Solutions

LELAND PIERCE

Associate Research Scientist and Lecturer

CoE Jon R. and Beverly S. Holt Award for Excellence in Teaching

PETER SEILER

Associate Professor

EECS Outstanding Achievement Award

FAWWAZ ULABY

Emmett Leith Distinguished University Professor Emeritus of EECS

CoE Edward Law Emeritus Outstanding Service Award

Paula Pernia Receives Staff Excellence Award

Paula Pernia, ECE Facilities Manager, received a Staff Excellence Award from the College of Engineering in recognition of her extraordinary efforts managing the facilities for Electrical and Computer Engineering, which extend beyond the EECS Building to include 140,094 sq. ft. of space in 10 different campus buildings.

“In addition to her responsibilities for the many facilities required for ECE, Paula manages an equipment inventory second only to the hospital, and with a department of ECE’s size, she handles more customers and requests than most,” said Lisa Armstrong, Unit Administrator.

ECE Staff Recognized for Contributions to ECE Community

Electrical and Computer Engineering’s culture of innovation, excellence, collaboration, and social equity is expressed in the work of seven recipients of the 2023 College of Engineering Staff Incentive Award.

These awards recognize staff who consistently demonstrate the College’s vision, mission and values, and who have demonstrated creativity, innovation and daring in helping the College build its culture of diversity, equity and social impact in engineering.

JEFFREY HOROSKO

ECE Purchasing Clerk

ELIZABETH OXFORD

Zeus Outreach Coordinator

EVA RUFF

ECE Administrative

Assistant Senior

DEVON DEGRAFFENREED

ECE Master’s Program Coordinator

ANN STALS

ECE Alumni

Engagement and Events Manager

EREMENTCHOUK Research Area Specialist Lead

EECS Course

Scheduling Coordinator

MIKHAIL

PUNAM VYAS

Dennis Sylvester, former Interim Chair, Paula Pernia, and Lisa Armstrong, Department Administrator

Solar Car Cruises to a 1st Place Finish in American Solar Challenge

The U-M Solar Car Team reclaimed its title as national champions in the 2024 American Solar Challenge (ASC), a 2,120 mile race from Tennessee to Wyoming that lasted 8 days this past July. This year’s car is called Astrum.

The team has now won a total of ten American Solar Challenges, which are held every other year. Prior to 2018, when they finished second, thy had crossed the finish line first for si consecutive races.

“It feels outstanding to be national champions again,” said Daniel Benedict, the team’s project manager and recent U-M computer engineering graduate. “For the past year, all of our consciousness has been dedicated toward this vehicle. All that hard work paid off, and I couldn’t imagine a better ending.”

One of the steps toward qualifying for the race is the Formula Sun Grand Prix, a track event that requires teams to complete a set number of laps. Eighteen laps in, while going around a sharp corner, Astrum tipped and rolled.

“It was scary, but because of how we had designed the car, I wasn’t injured at all,” said driver Naman Kabra, a rising junior studying electrical engineering.

Unfortunately, the car itself had to be repaired. With damage to the motor, their options were running out, until another team from Principia College in Illinois loaned them a spare motor and controller. Thanks in large part to their commitment to overcoming obstacles, as well as the help from Principia, they received approval to race in the ASC. Kabra was back behind the wheel for the big race, along with fellow EE students and drivers Charlie Tate and Daryl Day. For that race, it was smooth driving to a 1st place finish.

The U-M Solar Car and team after crossing the finish line in Casper, Wyoming. Photo: Holly Zumbrunnen

EE student Naman Kabra, one of three drivers in the competition. Photo: Holly Zumbrunnen

UM::Autonomy is the Top U.S Team at 2024 RoboBoat Competition

From the beach in Nathan Benderson Park, Florida, the 2024 UM::Autonomy team watched their boat, Phoenix, rise to fourth place—above all other U.S. teams in the annual RoboBoat competition. The team also took first place in the Design Competition portion of the event. Phoenix navigated through a course of floating buys, glided into a marked docking station, and sprayed water at a target as the team’s many months of hard work paid off.

Since 2007, the UM::Autonomy team has been entering a homemade autonomous boat to compete in a set of themed challenges at RoboBoat. This year’s challenges included hitting an image of a duck with water, and dropping objects into catch basins nicknamed “duck nests” and “beaver nests.”

To prepare for the 2024 race, the team opted to improve on the boat they had already built, and much of their work focused on the electrical system.

Electrical Lead and EE UG student Aayush Shah had his team completely overhaul the existing electrical system.

“We decided to use PCBs to make our electronics box smaller, since we had problems with the box and connections disconnecting the year before,” said Shah. “It was something I wanted to learn more about, and one of our members was well-versed in making PCBs already.”

“We’re continuously pushing for things to be more and more integrated,” added Eeshwar Krishnan, electrical team member, “So we’re learning a lot more about how we can take all these discrete subsystems that we used to buy and move them together, in house. We’re learning how to manufacture, test, and do consistent repeatability analysis of

electrical systems that we’ve never really touched before—that we didn’t have any reason to touch before.”

Students can learn these skills by seeking out additional classes and meetings with professors, but in practice they often learn from more experienced team members.

“After you’ve spent like a year on the team, you’ve learned what works and what doesn’t work, and that’s really helpful,” said computer engineering student Lani Quach, who is the incoming vice president. “In the process of starting from the beginning to gaining a leadership role, you can help lead new students and continue building on these foundations of learning.”

2024 UM::Autonomy team with The Phoenix

Aayush Shah (L) and Asheya Naik load Phoenix into the water. Photo courtesy UM::Autonomy

M-Fly’s Autonomous Aircraft Makes Team History

Building multiple aircraft to compete in annual competitions sounds like a job for aerospace engineers, and sure, it is. But when one of the competitions is called the Student Unmanned Aerial Systems (SUAS) Competition, and it’s hosted by RoboNation—then it also sounds like a job for EECS students, and it is!

M-Fly is a student team that builds aircraft to compete in the SAE Aero Design and SUAS competitions. This past year they brought two different aircraft to the SAE Aero Design East competition, and earned four trophies, including 3rd place overall in the Advanced Class.

Meanwhile, an entirely unique group of students were preparing for a different

challenge—flying an auonomous aircraft at SUAS.

This year’s team achieved something it had never done before—the honor of competing at the competition! And that happened with the help of Chief Engineer Yi Ling Wu and Autonomous Flight Systems Lead Eva Manabat, both undergraduate students studying computer engineering.

Wu and Manabat joined the M-Fly team as first ear students. Their grit, determination, and talent helped them rise quickly to leadership roles. It took three years for Wu and two years for the younger Manabat to make M-Fly history as members of that first team o compete at SUAS. They did this with the autonomous aircraft known as MAT-5, which they each had a hand in creating from the inside out.

Both Wu and Manabat would like to see more EECS students join the team.

“My grand vision for the EECS side of M-Fly is for us to design our own PCBs and to build our control software from

(L): Eva Manabat (Flight Systems Lead), Alyssa Cheslek (Hardware Lead), and Yi Ling Wu (Chief Engineer) at SUAS 2024.

“It was awesome, and a historic moment for M-Fly,” said Manabat. “We didn’t perform as well as we had hoped, especially due to the heat affecting our electronics, but we were all so excited to be there and we learned so much. It was a bonding experience that I will never forget.”

the ground up for our specific needs” said Wu. “Yes, it’s an aircraft, but we need EECS expertise for everything inside the aircraft.”

The MAT-5 did not win any awards, but it did compete, and that was enough to earn its place in M-Fly history.

M-Fly members of the Autonomous Plane subteam, with their aircraft MAT-5, at the 2024 Student Unmanned Aerial Systems Competition

Quant-UM Empowers Undergrads Interested in Quantum Science and Technology

Quant-UM is a new interdisciplinary student club that seeks to connect undergraduates across the university with quantum science resources and opportunities. It was started by EE undergraduate student Erin Diran-Ojo and Physics major David McDermott.

“There are all these quantum mechanisms informing the basic technology we use and the way we understand how things move in physics,” said Diran-Ojo. “That’s one of the main reasons why I’m interested in quantum, because it’s a way to go deeper into everything.”

Quantum science is already revolutionizing many classical technologies used across a variety of areas, including medicine, hardware and software development, finance, and machine learning. Because of quantum’s highly interdisciplinary nature and its potential to impact many different fields, Dian-Ojo and McDermott felt strongly that the club needed to be open and supportive to students from many different backgrounds, not just STEM. They are also partnering with the Quantum Research Institute.

“One of the goals of the university is to establish ourselves as a leader in both quantum research and quantum education,” said Prof. Alex Burgers, who serves as the faculty advisor for QuantUM. “We want the best quantum groups in the world to be recruiting our students, and supporting this club is absolutely helping that mission.”

Even if students don’t plan to pursue a career in quantum fields, being knowledgeable about the topics will be an invaluable asset in many different industries.

There are going to be a lot of people making promises about what quantum can do,” Burgers said. “We want our students to be able to think very critically about whether or not those promises are real, and this club will give our undergrads a really great way of having these meaningful conversations with people in both the industry and the academic sector.”

“There are going to be a lot of people making promises about what quantum can do. We want our students to be able to think very critically about whether or not those promises are real.”

– Alex Burgers, Quant-UM faculty advisor

Prof. Alex Burgers with inaugural board members Jeanie Qi, David McDermott, and Erin Diran-Ojo.

Photo: Miranda Howard

STUDENT SPOTLIGHTS

Amanda Liss Brings Sustainable Energy to a Small Village in Brazil

The Pantanal Partnership student group has as its mission using sustainable technology and community-oriented design to improve the quality of life for residents in the Pantanal region of Brazil. Both as an undergraduate student in Biomedical Engineering and as an ECE graduate student, Amanda Liss has been dedicated to their cause, and this past year she spearheaded a group trip to the region.

“This student organization has allowed me to blend my passion for sustainable technology with a commitment to global environmental conservation,” said Liss, who has served as a member, vice president, and president of the group.

Her greatest impact to the people of Brazil was the technology she helped develop. This included: development of

a small-scale hydropower water wheel for charging small electronics; creation of a less-expensive do-it-yourself charge controller for solar power systems; and installation of on-site solar power.

It’s likely that without Liss, the trip may never have happened. She helped keep the group afloat during the difficu COVID years, and when the group was finally able o travel post-COVID, Liss acted much like a CEO of a small startup. She led the team in securing significant funding for the poject, and used many resources available on campus in their preparation, such as 3D printers, electronic measurement equipment, and electronic and mechanical components available to students.

“I don’t know if the student organization would still exist if it hadn’t been for Amanda’s leadership during this time,” said Ethan Shirley, who has been active with the Pantanal Partnership since 2009.

The group will travel back to the communities from last summer’s trip to install several solar power systems and implement a more environmentallyfriendly waste incinerator.

(L) Team members Caleb Wegener, Amanda Liss, and Nathaniel Hodgson with the solar panels they installed for an indigenous village in the Xingu region of Brazil.

Amanda Liss installs a light switch powered by the newly-installed solar panel system.

Artificial Kelp Forests Weaken Impact of Extreme Weather

Combining interests in entrepreneurship and sustainability, undergraduate students Samantha Jayasundera and Jessica Beck teamed up to create a business plan for a company selling artificial elp forests. The technology would potentially benefit communities that live within 50 miles of a coast, which amounts to 50% of the nation’s population. They called their proposed company KelpNext, and came away with a total of $25K in prize money in the EnergyTech University Prize 2024 competition, sponsored by the U.S. Department of Energy Office o Technology Transitions.

Beck and Jayasundera learned of the potential benefitsof artificialkelp forests while preparing for the competition, which they entered after searching the internet for opportunities to pursue their mutual interests. The EnergyTech competition seemed like a good fit; it focused on high-potential energy technologies and also offered mentorship with a researcher in a national lab.

They came across the research of Dr. Nicole Mendoza at the National Renewable Energy Lab, who has been

making her own waves as a “supersonic environmentalist.” Part of Mendoza’s research was investigating the use of artificial elp forests to generate electricity.

“I was very excited when Samantha and Jessie reached out to me about all of the cool things they wanted to do with my kelp technology,” said Mendoza. “I was also ecstatic about supporting these two young, amazing women in STEM fields and seeing what innovative ideas and applications they came up with.”

Kelp is a type of seaweed that grows in both freshwater and saltwater relatively close to shore. An artificial elp forest could be manufactured and placed in similar locations to mimic some of the non-nutritional benefits of their natual counterparts. For example, an artificial kelp forest can trap nutrients, or build up

sediment where natural kelp forests or reefs have been damaged. It can also help reduce the strength of waves in stormy conditions. And not only would artificial elp forests hold up well during extreme storms, they could also provide potentially life-saving power following natural disasters.

“We pitched this primarily from an extreme weather preparedness and disaster relief perspective,” said Samantha Jayasundera, who just completed her second year as an undergraduate electrical engineering student. “Climate change is making storms worse, increasing their frequency and intensity. So while this is a product and a company that we are pitching, it also benefits humanit. We need to invest in things like this right now.”

Depiction of artificial kelp forests. Diagram: Dr. Nicole Mendoza, National Renewable Energy Laboratory (NREL)

Jessica Beck (left) and Samantha Jayasundera accept their honorary check after the EnergyTech University Prize competition.

Qualcomm Innovation Fellowship Supports Research on Intelligent Audio Systems

Imagine driving along, listening to a podcast through your car speakers while your road trip companion simultaneously takes a nap in silence. You can blast your podcast as loud as you like, and the sound would not bother someone in the passenger seat, just feet away.

This is one example of a scenario that ECE PhD students John Kustin and Vangelis Dikopoulos hope to achieve with their research. They won the 2024 Qualcomm Innovation Fellowship and $100K to make this a reality.

“Our proposal addresses the fundamental challenges of parametric sound in IoT devices through the design of an integrated circuit suitable for mass

production,” Dikopoulos said. “Our goal is to design a high-performance system that is very low-power, versatile, and capable of operating in a variety of acoustic environments.”

The audio Internet of Things (IoT) includes any device that interacts with users through voice commands or sound delivery. For example, smart speakers like Alexa and Google Home, smart earbuds, hearing aids, public announcement systems, and the Bluetooth sound systems in many cars are all part of the audio IoT.

However, as audio IoT devices become more widespread, users may look for more private or personalized listening

experiences, without the use of earbuds or headphones. Kustin and Dikopoulos are designing an integrated circuit that will enable parametric, or focused, sound for individual users in shared spaces. To achieve this, they use a technique called beamforming, which enables directional signal transmission.

Kustin and Dikopoulos are continuing their work in this area, under the supervision of their advisor Michael Flynn, the Fawwaz T. Ulaby Collegiate Professor of Electrical and Computer Engineering.

John Kustin (L) and Vangelis Dikopoulos. Photo: Jero Lopera

A Winning Plan for Green Hydrogen Trucking

People who care about organic food may be more likely to care about the environment, and therefore willing to pay a few extra cents to make sure it gets transported in an environmentally friendly way.

Banking on the truth of that statement, an interdisciplinary team of U-M students created a business plan for a transport company that could make a profit ven while relying on hydrogen fuel, which is a relatively clean, but costly, source of energy. They pitched their plan at the inaugural U-M Hydrogen Grand Challenge competition, and earned second place for their proposed company, Fresh-Air Freight.

“Long distance trucking seems to be one of the best applications for hydrogen transport,” said team member Rebecca Lentz, a doctoral student in Electrical and Computer Engineering, “because it becomes more efficient with longange, and filling the tank is a lot faster than going electric.”

The team then had to find a maret willing to pay the higher cost of using hydrogen-fueled trucks.

“The organic foods market has a customer base that is very interested in sustainability,” said Lentz. “It’s a market that’s continually increasing, and

there are organic farms in Michigan.” If customers are willing to pay a little extra for food transported in a way that is better for the environment, this becomes a profitable and green” business.

Individuals purchasing organic food have already resigned themselves to paying higher prices. The team believes they’d be willing to pay a bit more per item if they knew they were contributing to cleaner air. How much more? The team estimates that an apple that costs $1.19 with traditional transportation would rise to $1.37.

“Long distance trucking seems to be one of the best applications for hydrogen transport because it becomes more efficient with long range, and filling the tank is a lot faster than going electric.”

— Rebecca Lentz

L-R: Team members Marisa de Souza, Matthew Gerber, Fernando Villavicencio, Rachel Silcox, Rebecca Lentz. Not pictured: Jenna Stolzman.

Lightwave Electronics

Markus Borsch (PhD ECE 2023) received a 2023 ProQuest Distinguished Dissertation Award for his dissertation, Theory of Lightwave-Driven Quantum Electronics in Solids. Borsch’s research is focused on describing and predicting the movement of electrons that have been excited by light. Through his theoretical work and experiments with collaborators, he has described electron dynamics in solid matter with unprecedented spatial and temporal resolutions.

“One of the defining visions for this esearch is to develop solid-state-based quantum technologies that combine the existing infrastructure and scalability of semiconductor technologies with the advantage that quantum technologies can provide for communication, sensing, and computing,” said Borsch.

Borsch’s research has ties to the 2023 Nobel Prize in Physics, which was awarded to a team of researchers “for experimental methods that generate attosecond [one quintillionth of a second] pulses of light for the study of electron dynamics in matter.”

Borsch applied these methods to semiconductors, enabling rapid advancement in next-generation quantum technologies. His paper “Lightwave Electronics in Condensed Matter,” published in Nature Materials Reviews, was selected for a special Nature Collection that celebrates this Nobel Prize. He is currently a postdoctoral researcher working with his former advisor, Prof. Mack Kira.

Brain-Machine Interfaces

Joseph Costello received a Rackham Predoctoral Fellowship for his research that focuses on high performance, power efficient ain-machine interfaces to help those who suffer from sensorimotor impairments, including spinal cord injury, limb amputations, stroke, and neurodegenerative diseases.

“Tasks we take for granted like drinking from a cup, interacting with a phone, or communicating words can be challenging or impossible for individuals suffering the loss of limb mobility or speech,” explained Costello. “Brain-machine interfaces (BMIs) offer a promising solution for restoring mobility and communication.”

While BMIs have successfully controlled computer cursors and robotic arms, they are still limited in the accuracy of the decoding algorithm and consume too much power for an implantable system. Costello wants to fix these limitations

His research will focus on: (1) developing accurate decoding algorithms that work well in real-time, (2) optimizing the power consumption of the neural signal processing pipeline, and (3) applying these findings for posthetic control with human study participants. A recent project of his was to improve prosthetic hand function for people who have had upper limb amputation or paralysis. Costello is co-advised by Prof. Cynthia Chestek and Prof. David Blaauw.

JOSEPH COSTELLO

III-Nitride Semiconductors for Next Generation Electronics

Shubham Mondal received a Rackham Predoctoral Fellowship for his research into iII-Nitride semiconductors for next generation electronics and photonics. The research is expected to drive innovation in the fields of in-memoy computing, edge intelligence, quantum photonics, as well as high frequency, high power, and high temperature electronics.

III-Nitride semiconductors have gained significant attention in ecent years due to their qualities of having a wide and tunable direct bandgap coupled with strong spontaneous and piezoelectric polarizations, qualities that make them suitable for next-gen power electronics, optoelectronics, piezo electronics, and integrated photonics. The incorporation of rare earth elements can make conventional iIInitrides ferroelectric with significantly enhanced pieoelectric and nonlinear optical properties.

“Polarization makes iII-nitrides unique, and the ability to precisely control the polarization makes iII-nitrides attractive for UV-optoelectronics (LEDs, lasers, etc.) and power device (FETs, HEMTs, etc.) applications,” explained Mondal. “Going one step further, the ability to controllably switch the polarization, as is the case in recently discovered ferroelectric iII-Nitrides, opens up a new dimension in iII-nitrides for applications in the previously unexplored fields of data centric computing and edge intelligent devices.” Mondal is advised by Prof. Zetian Mi.

Analytical Wearables for Health Monitoring

Anjali Devi Sivakumar received a Rackham Barbour Scholarship for her research developing wearable devices for continuous health monitoring through insensible sweat. Insensible sweat (i.e., body odor), rich with valuable biomarkers and metabolites, shows immense potential as a diagnostic medium. The continuous and dynamic nature of insensible sweat makes it an excellent candidate for integration into wearable diagnostic systems. Sivakumar hopes that the devices she is developing will improve healthcare accessibility and enhance preventive healthcare measures, even in the most remote regions.

“In recent years, there has been a significant upsuge in the popularity and emphasis on utilizing wearable diagnostic devices for continuous health monitoring,” stated Sivakumar. “I am developing wearable analytical devices tailored for the investigation of insensible sweat and its medical significance acoss various diseases.”

The first pat of Sivakumar’s research includes developing a wearable hygrometerbased transepidermal water loss measurement device that has applications in tracking food allergies and diagnosing dermatological conditions. The second part is focused on developing a low-power, low-cost wearable micro-gas chromatography device, approximately the size of a smartphone, to analyze the volatile organic compounds in the insensible sweat. She will be collaborating with clinicians at Michigan Medicine and the data scientist team at Max Harry Weil Institute for Critical Care Research and Innovation. Sivakumar is co-advised by Biomedical Engineering Prof. Xudong (Sherman) Fan and Prof. Zhaohui Zhong.

SHUBHAM MONDAL

ANJALI DEVI SIVAKUMAR

STUDENT HONORS + AWARDS

ALYSSA ANDERSON

Undergraduate EE Student

EECS Outstanding Achievement Award

MIRANDA BALTAXE

Undergraduate CE Student

EECS Commercialization/ Entrepreneurship Award

ELIJAH BECKER

Undergraduate CE Student

EECS Community Impact Award

AVA CHANG

Undergraduate CE Student

Tau Beta Pi First Year Student Award

AADITYA HAMBARDE

Doctoral Student

Rackham Outstanding Graduate Student Instructor Award

ANYUN HSU

Undergraduate EE Student

William Harvey Seeley Prize

INHWI HWANG

Doctoral Student

IEEE PELS John G. Kassakian Fellowship

IEEE PELS Graduate Studies Fellowship

ILHAM ISLAM

Undergraduate CE Student

EECS Outstanding Service Award

BRINDA KAPANI

Undergraduate EE Student

EECS Collaboration, Respect, and Inclusion Award

NOUMAN KHAN Doctoral Student

CoE Richard and Eleanor Towner Prize for Distinguished Academic Achievement

DORA KUFLU

Undergraduate CE Student

EECS Collaboration, Respect, and Inclusion Award

AUSTIN LIN Doctoral Student

Prize Conference Paper Award (IEEE Power & Energy Society)

AMANDA LISS Master’s Student

CoE Harry B. Benford Award for Entrepreneurial Leadership

AMY LIU

Undergraduate EE Student

William L. Everitt Student Award of Excellence

ANDREA LIU

Undergraduate CE Student

CoE Distinguished Academic Achievement Award

William L. Everitt Student Award of Excellence

JIANGNAN LIU

Doctoral Student

Society of Vacuum Coaters Foundation (SVCF) Scholarship

DUNCAN MADDEN Doctoral Student

2024 Ernest K. Smith USNC-URSI student paper competition, 2nd place

JOSEPH MAFFETONE

Undergraduate CE Student

EECS Outstanding Achievement Award

JOSÉ LUIZ VARGAS DE MENDONÇA

Undergraduate CE Student

EECS Outstanding Research Award

SHUBHAM MONDAL

Doctoral Student

Society of Vacuum Coaters Foundation (SVCF) Scholarship

2023 APL Materials rst-place Excellence in Research Award

ADITYA VARMA MUPPALA

Doctoral Student

CoE Richard F. and Eleanor A. Towner

Prize For Outstanding GSI

CoE Richard F. and Eleanor A. Towner

Prize For Outstanding Ph.D. Research

SAMUEL NOLAN

Undergraduate EE Student

CoE Distinguished Academic Achievement Award

EECS Community Impact Award

ANDREW PARK Doctoral Student

iWAT Student Paper Award, 1st place (2024 Int. Workshop in Antenna Technology

TIFFANY PARISI

Master’s Student

Excellence in ECE Honor Roll

MATT RAYMOND Doctoral Student

Excellence in ECE Honor Roll

J. Robert Beyster Computational Innovation Graduate Fellowship

JEREMY SHEN

Undergraduate EE Student

EECS Outstanding Research Award

William Harvey Seeley Prize

DAVID SHEPPARD

Undergraduate CE Student

Excellence in ECE Honor Roll

ANJALI DEVI SIVAKUMAR

Doctoral Student

Excellence in ECE Honor Roll

YIXIN XIAO Doctoral Student

AVS Dorothy M. and Earl S. Hoffman Scholarship

AMANDA WHITLEY

Undergraduate EE Student

EECS Outstanding Service Award

KEVIN ZHENG

Undergraduate EE Student

EECS Commercialization/ Entrepreneurship Award

ALUMNI SPOTLIGHTS

MO FAISAL Builds the Successful Semiconductor Company, Movellus

Mo Faisal (MSE PhD, EE), founder and CEO of Movellus Inc., received the 2023 ECE Rising Star Alumni Award for building his successful semiconductor company while still early in his career.

Movellus is based on research Faisal originally conducted at U-M with his advisor, Prof. David Wentzloff. Faisal designed synthesizable clock generator technology that is smaller, cheaper and faster than existing solutions. Clock generators are found in microprocessors, which are found in most every electronic device imaginable, from televisions to smart phones to refrigerators to thermostats. His technology also made it possible to shrink the design time by 80%, allowing for a much faster time to market.

“It really is a fundamental innovation that touches almost every electronic device out there.”

Faisal then teamed up with Jeff Fredenburg (BSE MSE PhD EE), a fellow ECE PhD student at the time. Together, they entered their proposal for a company based on Faisal’s research into the 2014 Michigan Business Challenge—which they won.

“In school, in a research setting, you have to get one or two chips working, and you’re happy to be publishing,” Faisal said. “The real world doesn’t work like that. You have to ship one billion units, and all of them have to work.”

Faisal and his team launched Movellus in 2014 and today, Movellus is a leader in System-on-a-Chip (SoC) clocking, droop detection, and mitigation, which are enabling the next generation of complex SoCs in AI and mobile device technologies, as well as the automotive and aerospace industries.

Faisal initially designed his clock generators to work in three areas: Bluetooth, wireless wearable electronics, and microprocessors for the Internet of Things (IoT). The clock that he designed for IoT applications consumes just nano-watt levels of power. Since the initial days the core technology of synthesizable analog has expanded to include clock generation, droop detection and mitigation, and general on-chip sensors. The technology has been deployed in many areas, including AI and IoT, as well as automotive applications and on satellites.

With high aspirations, Faisal says, “Soon, if you’re driving a car, you’ll be driving a car with Movellus technology in it. If you’re using a smartphone or smart devices in your home, they’ll have Movellus technology. When you connect to Wi-Fi, it will go through Movellus technology. It really is a fundamental innovation that touches almost every electronic device out there.”

Watch Faisal’s talk

Mo Faisal showing his winnings from the 2014 Michigan Business Challenge.

RHONDA FRANKLIN is a Distinguished Educator who Believes in the Power of Mentoring

Rhonda Franklin (MS PhD EE), McKnight Presidential Professor of Electrical Engineering in the Department of Electrical and Computer Engineering, and Abbott Professor of Innovative Education in the Institute for Engineering in Medicine at the University of Minnesota, was recognized for her exceptional contributions to engineering education with the 2022 ECE Distinguished Alumni Educator Award. She was able to come give her talk this past year.

Franklin was a member of the Radiation Lab while a graduate student at Michigan. Studying under Prof. Linda Katehi inspired her future research directions as well as a lasting desire to develop and mentor a diverse research group of her own.

“If you believe diversity is going to give you better outcomes then you have to teach people how to do it,” said Franklin. “Prof. Katehi taught us to be highly productive within a diverse group. We were all very, very different. But we could be whatever we were and somehow she could see how to manage us and lead us in a way that we could be very productive and successful without ever having to not be who we were.”

“I like working with things-for-things but I really wanted to do things-for-people.”

Her research allows her to help people in a direct and tangible way. As she put it, “I like working with things-for-things but I really wanted to do things-for-people.”

For the past 11 years, Franklin has been helping undergraduate and early graduate students to take advantage of networking opportunities through a program called Project Connect, sponsored by the International Microwave Symposium. She founded Project Connect with two other former colleagues at Michigan, Prof. Rashaunda Henderson at UT Dallas, and Tom Weller, Michael and Judith Gaulke Chair in Electrical Engineering and Computer Science at Oregon State University.

Franklin’s own diverse research group at the University of Minnesota focuses on microwave packaging and circuit technology for communications systems, sustainable ecology, biomedical applications, and most recently, security.

In recognition of her service to the community and positive influence on a dveloping a diverse workforce, Franklin received the 2021 IEEE MGA Diversity and Inclusion Award, the 2021 George W. Taylor Award for Distinguished Service, the 2019 IEEE N. Walter Cox Service Award, the 2018 Minnesota African American Heritage Calendar Award, and the 2017 John Tate Advising Award.

Watch Franklin’s talk

Franklin at the reception for her PhD dissertation defense.

CURTIS LING Grows the Fabless Company MaxLinear to International Success

Curtis Ling (MS PhD EE), founder and CTO of MaxLinear, Inc., received the 2023 ECE Alumni Merit Award in recognition of his distinguished two-decade career at MaxLinear.

Ling’s entrepreneurial talent was shown early in days as a graduate student at Michigan when he helped his advisor, Prof. Gabriel Rebeiz, build a lab and research group from scratch. After graduating, Ling joined the faculty of the newlyestablished Hong Kong University of Science and Technology. As an early faculty member, he was given the freedom to develop his research and shape the new department.

In 1999, he returned to California to gain industry experience in product development. He served as a principal engineer at the startup, Silicon Wave, Inc., to help build the world’s first single-chip Bluetooth transceivers. Silicon Wave’s assets were ultimately acquired by Qualcomm, which successfully took the Bluetooth chips to volume production.

“It’s been said that, ‘You don’t climb your way to success,’ your team carries you there, and that’s certainly been true in my experience.”

In 2003, he and seven other colleagues left to start their own company, which became MaxLinear, a fabless semiconductor startup developing communication systems on silicon. Today, the company continues to advance state of the art high-performance broadband integrated circuits. They have offices ound the world—across North America, Europe, the Middle East, and Asia.

“It’s been said that, ‘You don’t climb your way to success, your team carries you there,'” Ling said, “and that’s certainly been true in my experience.”

When Ling’s team began marketing the company’s capabilities in its early days, Panasonic was the first o express interest in their idea of a low-power, single-chip

television receiver. This precipitated MaxLinear’s transition from providing consulting services, to committing the team entirely to product development. Once they had a prototype, the team was able to attract venture funding in 2004. They became publicly listed in 2010.

MaxLinear was among the first companies o build broadband communication chips with analog, RF and mixed-signal interfaces in generic digital CMOS processes, benefiting fom high gate density and low cost. Their products are now found in cable modems and home gateways, cellular base station towers, and datacenters.

During his lecture, Ling stressed that, from a technology perspective, MaxLinear is a tale of how the chip industry successfully integrated high performance communication systems in mass production CMOS processes in a period of 25 years. This effectively brought Moore’s Law into contact with antennas and photonics.

This transformation was happening concurrently with an explosive growth in wireless and datacenter infrastructure markets. It was also during this period that the fabless semiconductor industry grew from relative obscurity to strategic importance—and ultimately the center of national attention.”

Watch Ling’s talk

Dr. Curtis Ling (left) was presented with the 2023 ECE Merit Alumni Award by Sr. Assoc. Chair Anthony Grbic at Ling’s award lecture on September 22, 2023.

OLGA MILENKOVIC has led a Distinguished Career as an Educator

Olgica Milenkovic (MS Math and PhD EE:Systems), the Franklin W. Woeltge professor of Electrical and Computer Engineering at the University of Illinois, Urbana-Champaign (UIUC), received the 2023 ECE Distinguished Educator Award for her exceptional contributions to educating the next generation of electrical and computer engineers.

“At some point, you start measuring your success and the quality of your achievements through your students,” Milenkovic said. “Everything becomes about how well your students did. How well are their publications received? Did they get their career awards? That is the best thing, at least in my experience, to observe and cherish.”

Milenkovic heads a research group at UIUC that spans the areas of algorithm design and computing, bioinformatics, coding theory, machine learning and signal processing. She specializes in DNA storage, compressive sensing, low rank matrix completion, community detection, hypergraph clustering, and ordinal data processing.

Her most recent work is on new higher-order clustering algorithms, also known as motif or hypergraph clustering techniques. Her team has presented their work at top machine learning conferences, such as Neural Information Processing Systems (NeurIPS) and International Conference on Machine Learning (ICML), including a “Spotlight” presentation at the NeurIPS 2017 conference.

She has received many awards, including the NSF CAREER Award, the DARPA Young Faculty Award, the Dean’s Excellence in Research Award, and several best paper awards. In 2013, she was elected a UIUC Center for Advanced Study Associate and Willett Scholar. She was elected Distinguished Lecturer of the Information Theory Society in 2015, and is an IEEE Fellow.

ALUMNI SPOTLIGHTS

“At some point, you start measuring your success and the quality of your achievements through your students.”

Milenkovic fondly recalled her time at Michigan, and what brought her here. When trying to decide where to go for her graduate education, she asked her friend, Steve Mclaughlin, for his advice. Mclaughlin, the current Provost and Vice President for Academic Affairs at the Georgia Institute of Technology, is also an ECE alum. He told her, “It’s a nobrainer. You have to go to Michigan.”

As an immigrant from Yugoslavia, Milenkovic loved exploring the history and culture of Ann Arbor. All these years later, she says, “At Michigan, you make friends for life. I wish that the world would take a template from Ann Arbor, because this is a very special place where you put aside all your differences. My best friends from Michigan were people of all religions and all ethnic backgrounds, and we got along amazingly well. Nothing would stand in the way of our friendship.”

Watch Milenkovic’s talk

KLA CEO and President RICK WALLACE Embraces Challenges and Champions Values

Rick Wallace (BSE EE) received the 2023 ECE Alumni Impact Award in honor of his distinguished career leading the international semiconductor manufacturing company, KLA, Inc.

After graduating from Michigan, Wallace worked at P&G, but found himself looking for something different—perhaps in Silicon Valley. So he sent 100 resumes to different companies in the area, and received in return 100 rejections.

Rather than give up, he thought, “Gee, I need to go there. So, I sold everything I had, and I drove my Camaro T-top out to California.”

He landed an interview at Cypress Semiconductor, and had his final inteview with the founder of the company.

“Companies that are successful over the long term often do not have charismatic leaders. They have systems in place, and they have values.”

“One of first things the founder said, was, ‘ait, you’re an EE from Michigan?’” Wallace said. “It became pretty clear in that meeting that the degree was valued. I got the job.”

While at Cypress, Wallace realized he needed to learn more about semiconductor technology. He enrolled in a Masters of Engineering program at Santa Clara University in 1985, which was designed for working professionals in Silicon Valley.

“Once again, I was thankful for my Michigan degree, because I realized that I was well prepared to resume my engineering studies, even though it had been fie years,” Wallace said.

Wallace gained further experience at Ultratech Stepper before joining KLA as an Applications Engineer in 1988. He progressed through many different roles at KLA, including various technical marketing positions, before transitioning to business leadership responsibilities.

He became President and CEO of KLA in 2005. Under his leadership, KLA has grown into a Fortune 500 semiconductor

manufacturing equipment company with products that help enable the future of everything from AI to next generation chip design. KLA was recently recognized by TIME Magazine as one of the world’s best companies and by Newsweek as one of America’s greenest companies.

KLA opened a new North American headquarters office i Ann Arbor in 2021. Michigan Gov. Gretchen Whitmer gave a talk at its grand opening, along with Rick Wallace.

“We’re in a war for talent, so we have to create an environment like this that’s attractive for people,” said Wallace at the event. “We also have to have a community that is desirable for people to live in. Ann Arbor punches well above its weight. It’s a great place to live. It’s a great place to grow a family.”

During his award talk, Wallace stressed the two crucial qualities a company needs to be successful: the ability to adapt and evolve as the world changes, and an ability to persevere through setbacks.

“Companies that are successful over the long term often do not have charismatic leaders,” Wallace said. “They have systems in place, and they have values. And those are the things that propel them, so that it’s not about the one person, the one ego.”

Watch Wallace’s talk

Prof. Dennis Sylvester (L), former interim chair of ECE, presented the 2023 ECE Alumni Impact Award to Rick Wallace on November 10th, 2023.

ECE COUNCIL

MUHAMMAD FAISAL

CEO and Founder, Movellus

RJ JAIN

Founder & CEO, Price.com

SHIRIN MANGOLD

VP of IT Service Delivery and Facilities, Deltek Inc.

K. CYRUS HADAVI Founder & CEO, Adexa, Inc.

JOHN MACILWAINE CEO, Highnote

ISAAC PORCHE

Mission Area Executive, National Security Analysis, The Johns Hopkins University Applied Physics Laboratory

CFO, Humanetics Group

BOB STEFANSKI

Founder and Managing Director, eLab Ventures

RASHAUNDA HENDERSON

Professor, The University of Texas at Dallas

PRASHANTH MAHENDRA-RAJAH CFO, Uber

LEON PRYOR

Senior Game Producer, Meta

SAL TRUPIANO Senior Director, Engineering Services, QNX Software Systems

The ECE Council (ECEC) is a prestigious group of alumni and friends of the department who are committed to ECE’s goal of being a national and global nexus of positive, transformational change across all industries.

The ECEC provides guidance and help with key priorities, including alumni engagement, industry engagement, development, diversity, entrepreneurship, education innovation, and future initiatives.

MITCHELL ROHDE

ECEC Chair

Founder and President, Rohde Way, LLC

Founder and Former CEO, Quantum Signal AI, LLC

DAWSON YEE

Former System Engineer, Azure Hardware, Quantum Computing, Microsoft

NAVIN SHENOY Former Executive VP and General Manager, Data Platforms Group, Intel Corporation

Director, EV Utilities Programs, Ford Motor Company

AMIT SINGHI

LINDA ZHANG

GIVING SPOTLIGHT

CHEN-LUAN FAMILY Faculty Development Professorship

Enke Chen (EE:S MSE PhD 1987 1991) and Huiyi Luan established the Chen-Luan Family Faculty Development Professorship to support early and mid-career faculty in ECE. The first ecipient is Necmiye Ozay.

This is the first faculty dvelopment professorship fund in ECE, and it was dedicated in honor of Chen’s PhD advisor, Stéphane Lafortune, the N. Harris McClamroch Professor of Electrical Engineering and Computer Science.

“Stéphane has always been a role model for me, and his mentoring has benefited me thoughout my whole career,” Chen said. “He taught me how to approach and analyze problems and how to pay attention to details and work hard. He inspired me to explore and expand my knowledge and skills.”

After graduating from U-M, Chen joined Merit Network, a consortium hosted at U-M, that was transforming

NSFNET into the fastest and most reliable network of its time. He gained further experience at MCI, where he worked on the Internet-MCI backbone.

Chen was one of the key contributors in the development of routers in the Internet, in particular routing algorithms such as the Border Gateway Protocol. He also was an expert in networking system architecture, design, and implementation, with emphasis on the control-plane robustness, scalability, and modularity.

“Enke’s career has been truly remarkable,” said Lafortune. “He was at the center of the action when the Internet was privatized and he was involved in the design of the routing infrastructure that allowed the exponential growth of the Internet. I feel immense pride at all his accomplishments.”

Chen spent most of his career at Cisco, and in 2020, he joined Palo Alto Networks as a Senior Distinguished Engineer. He’s been working on the architecture and design of advanced networking and secure access solutions.

Luan earned her Master’s degree in Mathematics with a concentration in computer science from Eastern Michigan University. She worked for a number of years as a software engineer and as a Database Administrator for several institutions, including the University of Michigan, Unisys, and Lockheed Martin. For the past twenty years, she has been working as a real estate investor and property manager. She also participates in several charitable initiatives for teachers and students with financial hadship.

“Michigan is a great university, and Ann Arbor is a very nice place to live,” Chen said. “We had eight wonderful years here, and our son Gregory was born at the U-M hospital. Over the years we have been thinking about contributing back to Michigan, and to ECE specificall.”

The department is deeply grateful for Huiyi Luan’s and Enke Chen’s support of its mission and faculty.

Huiyi Luan (L) and Enke Chen

GIVING SPOTLIGHT

KRUMM FAMILY Scholarship Fund

Charles “Chuck” Krumm (BS MS PhD ECE 1963 1965 1970) and Patrick Krumm established the Krumm Family Scholarship Fund with a bequest to support graduate education in Electrical and Computer Engineering.

“Scholarships are gifts that keep on giving,” said Krumm. “Funds that can initially support a single scholarship can grow, through investment, to support many students over generations.”

Chuck Krumm was a transfer student to the University of Michigan, and enjoyed the education he received not just from the faculty and through the world-class facilities, but from his fellow students.

“Each student brings their own perspective and cultural heritage,” he said, “offering their peers the opportunity to gain a better understanding of the world at large.”

It was at Michigan that Charles met his wife, Patricia. They met during their graduate school years, Chuck in engineering and Patricia in speech pathology.

Chuck’s professional career began at Raytheon, where he led a team developing gallium arsenide (GaAs) field effect transistors (FET). Later, while at Hughes Research Labs, he led a team developing GaAs device technologies for aircraft and space applications. This effort produced the first GaAs FT amplifier working abve 30 GHz and a digital flip-flop with a clock equency of 15 GHz, which was a world record at the time.

In 1989, he was invited to lead a diverse team of aerospace companies and their suppliers as part of a large government effort to upgrade U.S. capability in GaAs monolithic microwave integrated circuits. Many of the technologies he helped develop have been put into radar systems used by the Air Force, Army, and Navy.

Chuck later joined Conexant to manage the manufacturing operation that produced GaAs cell phone power amplifiers.This activity merged with Alpha Industries to become Skyworks, which is now one of the world’s largest producers of these devices.

“As innovators, we often fail to pause and consider the ramifications of each incemental change that we make,” said Krumm. “Often, the societal impacts of any particular innovation are not immediately evident. Nevertheless, I believe we are all responsible for ensuring that our developments are used for the overall benefit of societ. That work is challenging and will undoubtedly require a highly skilled and well-educated workforce. Fortunately, Michigan is very well suited to address larger societal issues and train the incoming generations of students.”

Krumm is helping prepare the future workforce with this fund. And he hopes the tradition will continue.

“One can hope that the students who are supported by these scholarships,” said Krumm, “will be motivated later in their careers to continue this philanthropic tradition.”

This is the second scholarship fund initiated by Krumm. The department is deeply grateful for the Krumm Family’s support of its students.

Patricia and Charles Krumm

ECE FACULTY

Current tenure and tenure track faculty, research scientists, and regular lecturers active as of September 1, 2024

Afshari, Ehsan Professor Ali, Maha Lecturer III

Anastasopoulos, Achilleas Assoc. Professor

Balzano, Laura Assoc. Professor (courtesy: STATS)

Benken, Alexander Research Investigator

Blaauw, David T. Kensall D. Wise Collegiate Professor of EECS

Burgers, Alexander Asst. Professor

Campbell, Paul Asst. Research Scientist

Chen, Jiasi Assoc. Professor

Cook, Jeffrey Lecturer II

Corso, Jason Professor, ROB and EECS

Deotare, Parag Assoc. Professor (courtesy: AP)

Dick, Robert Professor

Dvorkin, Vladimir Asst. Professor

Eid, Aline Asst. Professor

Florian, Matthias Research Investigator

Fessler, Jeffrey William L. Root Dist. Univ. Prof. of EECS; Interim Chair of ECE; (courtesy: BME, RAD)

Finelli, Cynthia David C. Munson, Jr. Collegiate Prof. of Eng.; Director, EER Program (courtesy: Education)

Flynn, Michael Fawwaz T. Ulaby Collegiate Professor of ECE

Galvanauskas, Almantas Professor

Garmire, David T. Assoc. Research Scientist Lecturer III

Gianchandani, Yogesh B. Professor; Director, WIMS2 (courtesy: AP, ME)

Forrest, Stephen R. Peter A. Franken Dist. University Prof. of Eng.; Paul G. Goebel Professor; (courtesy: PHY, MSE, AP)

Freudenberg, James S. Professor

Giebink, Chris Professor (courtesy: PHY) Gilchrist, Brian E. Professor (courtesy: CLASP, AP)

Grbic, Anthony John L. Tishman Prof. of Eng.; Sr. Assoc. Chair; (courtesy: AP)

Jay Professor (courtesy: AP, MACRO, ME)

Hero, Al John H. Holland Dist. Univ. Prof.; R.J. and B. Williams Professor of Engineering (courtesy: BME, STATS )

Kim, Hun-Seok

Samuel H. Fuller Early Career Prof. of ECE; Assoc. Professor

Kira, Mackillo Professor; Co-director, Quantum Research Institute (courtesy: PHYS)

Ku, Pei-Cheng Professor; Assoc. Chair, Undergraduate Affairs

Kushner, Mark J. William P Allis Dist. Univ. Prof. of EECS; George I. Haddad Professor; Director, MIPSE (courtesy: AP, ChemE, NERS)

L.

Lafortune, Stéphane N. Harris McClamroch Collegiate Professor of EECS

Hou, Bixue Assoc. Research Scientist

Incer, Inigo Asst. Professor

Islam, Mohammed N. Professor (courtesy: BME)

Jeong, Seokhyeon Asst. Research Scientist

Kanicki, Jerzy Professor (courtesy: AP)

Kim, Gyouho Asst. Research Scientist

Li, Jing Shuang (Lisa) Asst. Professor

Li, Yongxi Assoc. Research Scientist

Liang, Di Professor (courtesy: AP)

Liu, Bin Asst. Research Scientist

Liu, Shuai Asst. Research Scientist

Liu, Zhongming Assoc. Professor, BME and EECS

Guo,

Hofmann, Heath Professor (courtesy: NAME)

Liu, Mingyan Alice

Hunt Collegiate Prof. of Eng.; Assoc. Dean for Academic Affairs

Norris, Theodore B. Gérard A. Mourou Professorof EECS; (courtesy: AP)

Owens, Andrew Asst. Professor

Oymak, Samet Asst. Professor

Ozay, Necmiye Chen-Luan Family Faculty Dev. Prof. of ECE; Assoc. Professor, EECS and ROB

Peterson, Becky (R.L.) Assoc. Professor; Director, LNF (courtesy: AP MSE)

Pierce, Leland Assoc. Research Scientist; Lecturer II

Pradhan, S. Sandeep Professor Qin, Yutao Assoc. Research Scientist

Qu, Qing Asst. Professor

Revzen, Shai Assoc. Professor (courtesy: EEB)

Saligane, Mehdi Asst. Research Scientist

Sarabi, Armin Asst. Research Scientist

Scott, Clayton D. Professor (courtesy: STATS)

Seiler, Peter Assoc. Professor; Assoc. Chair for Graduate Affairs

Shekhar, Shubhanshu Asst. Professor

Shen, Liyue Asst. Professor

Subramanian, Vijay Assoc. Professor

Lopez Ruiz, Jose Roberto Research Investigator

Lu, Wei James R. Mellor Prof. of Eng. (courtesy: AP, MSE)

Maksimchuk, Anatoly Research Scientist

Mathieu, Johanna Assoc. Professor; Director, Institute for Energy Solutions

Mazumder, Pinaki Professor Mi, Zetian Professor

Michielssen, Eric Louise Ganiard Johnson Prof. of Eng.; Assoc. Dean for Research

Mortazawi, Amir Professor; Director, RADLAB

Nadakuditi, Rajesh Rao Assoc. Professor (courtesy: AP)

Nashashibi, Adib Assoc. Research Scientist

Nees, John Research Scientist

Najafi, Khalil Schlumberger Prof. of Engineering; Arthur F. Thurnau Professor (courtesy: BME)

Sarabandi, Kamal Fawwaz T. Ulaby Dist. Univ. Prof.; Rufus S. Teesdale Prof. of Engineering

Winful, Herbert

Joseph E. & Anne P. Rowe Prof. of EE; Arthur F. Thurnau Prof.; Univ. Diversity and Social Transformation Prof. (courtesy: AP, PHY)

AFFILIATED FACULTY

Includes faculty who are paid entirely by another department or division, but have an official affiliation with

Austin, Todd. S. Jack Hu Professor of CSE

Berenson, Dmitry. Assoc. Professor, ROB Brehob, Mark. Kurt Metzger Lecturer, CSE Chestek, Cynthia. Assoc. Professor, BME Cundiff, Steven. Harrison M. Randall Professor of Physics, PHY

Deng, Hui. Professor, PHY

Epureanu, Bogdan. Professor, ME Fan, Sherman. Richard A. Auhll Prof., BME

Goldman, Rachel. Maria Goeppert Mayer Professor, MSE

Gong, Xiwen. Asst. Professor, ChemE

Gregg, Robert. Assoc. Professor, ROB Krushelnick, Karl. Harry J. Gomberg Professor, NERS McBride, Ryan. Professor, NERS

AERO – Aerospace Engineering

AP – Applied Physics

BioPHY – BioPhysics

BME – Biomedical Engineering

CEE – Civil and Environmental Engineering

ChemE – Chemical Engineering

CLASP – Climate and Space Sciences and Engineering

CSE – Computer Science and Engineering

EEB – Ecology and Evolutionary Biology

IntMed – Internal Medicine

IOG – Institute of Gerontology

Nielsen, Jon-Fredrik. Assoc. Research Scientist, BME

Pipe, Kevin. Professor, ME

Reddy, Pramod Sangi. Professor, ME

Sakallah, Karem. Professor, CSE

Sample, Alanson, Assoc. Professor, CSE

Scruggs, Jeffrey. Assoc. Professor, CEE

Shin, Kang. Kevin and Nancy O’Connor Professor, CSE Stefanopoulou, Anna. William Clay Ford Prof. of Technology, ME Sun, Jing. Michael G Parsons Professor, NAME Thomas, Alexander. Professor, NERS

Tilbury, Dawn. Ronald D and Regina C McNeil Chair, ROB Violi, Angela. Professor, ME Z, Y. Professor, NERS

MACRO – Macromolecular Science and Engineering

ME – Mechanical Engineering

MSE – Materials Science and Engineering

NAME – Naval Architecture and Marine Engineering

NERS – Nuclear Engineering and Radiological Sciences

OTO – Otolaryngology

PHY – Physics

RAD – Radiology

ROB – Robotics

STATS – Statistics

Sylvester, Dennis Edward S. Davidson Collegiate Prof. of ECE

Tang, Wei Asst. Research Scientist

Terry, Fred Professor (courtesy: AP)

Tsang, Leung Robert J. Hiller Prof. of Engineering

Wang, Ding Asst. Research Scientist

Wentzloff, David D. Professor; Director, Michigan Integrated Circuits Lab

Willingale, Louise Assoc. Professor

Wu, Yuanpeng Research Investigator

Xu, Mengyue Research Investigator

Ying, Lei Professor

Yoon, Euisik Professor (courtesy: BME, ME)

Young, Steven Asst. Research Scientist

Zhang, Bingxing Asst. Research Scientist

Zhang, Pei Assoc. Professor

Zhang, Zhengya Professor

Zhang, Zheshen Assoc. Professor Zhong, Zhaohui Assoc. Professor

1301 Beal Avenue

Ann Arbor, Michigan 48109-2122

ece.engin.umich.edu

Photo: Silvia Cardarelli