2022 Swanson School Department of Electrical and Computer Engineering Newsletter by PITT

ECE NEWS WINTER 2022

ELECTRICAL & COMPUTER ENGINEERING

A Computational Look at How Genes Change the Human Brain

ssistant Professor Liang Zhan received a $500,000 CAREER award from the National Science Foundation to develop computational tools that improve our understanding of the human brain.

In this project, he will leverage brain modular structure to study brain imaging genetics and develop new computational tools to illuminate how genetic factors impact brain structure and function. Researchers can use this technology to examine how specific genes, or their variants, affect neural systems and contribute to brain disorders. Zhan’s team will specifically study Alzheimer’s disease – a condition that currently affects 5.8 million Americans and is projected to nearly triple to 14 million people by 2060. “There is no clear evidence to show how Alzheimer’s disease develops,” said Zhan. “Researchers are developing a variety of methods to uncover the mechanisms behind Alzheimer’s onset and progression, but we lack effective computational tools.” Though this work focuses on Alzheimer’s disease, the proposed tools can be applied to other brain research as well. “Current brain imaging genetics studies assume a one-to-one linear relationship between genes and imaging features, but linearity is too simplistic and does not allow researchers to identify high-level patterns,” explained Zhan. “Additionally, MRI research often focuses on small regions of the brain, which reduces the complexity of the imaging down to one-dimension and discards important information on brain dynamics. Instead, my group will focus on characterizing higher-level brain network features.”

2021 NSF CAREER Award Winner

Annual Publication of the University of Pittsburgh Swanson School of Engineering

Synthesizing an Artificial Synapse for Artificial Intelligence

n science fiction stories from “I, Robot” to “Star Trek,” an android’s “positronic brain” enables it to function like a human, but with tremendously more processing power and speed. In reality, the opposite is true: a human brain – which today is still more proficient than CPUs at cognitive tasks like pattern recognition – 2020 NSF CAREER Award Winner needs only 20 watts of power to complete a task, while a supercomputer requires more than 50,000 times that amount of energy. For that reason, researchers are turning to neuromorphic computers and artificial neural networks that work more like the human brain. However, with current technology, it is both challenging and expensive to replicate the spatio-temporal processes native to the brain, like short-term and long-term memory, in artificial spiking neural networks (SNN). Feng Xiong, assistant professor, received a $500,000 CAREER Award from the National Science Foundation for his work developing the missing element, a dynamic synapse, that will dramatically improve energy efficiency, bandwidth and cognitive capabilities of SNNs.

Read more about this on page 3

engineering.pitt.edu/ece

Letter from the Chair Dear friends and colleagues, I am honored to report on the very productive and successful calendar year 2021 completed by our department. We enter 2022, the 129th anniversary of our department’s founding by engineering pioneers George Westinghouse and Reginald Fessenden, providing highly innovative undergraduate and graduate programs and world-class research centers and laboratories. In Pitt ECE, we combine theory with practice at the nexus of computer and electrical engineering, enabling our students to learn, develop, and lead lives of impact. The foundation of our department is its undergraduate programs in electrical engineering and computer engineering, presently serving enrollments of about 200 and 300, respectively. Over the past several years, these programs have been transformed to dramatically improve their breadth and depth for our students. Major changes include: (a) a sophomore year common to both majors consisting of two-course sequences in analog hardware, digital hardware, software design, and analytical methods, all taught entirely in our department as a comprehensive foundation; (b) a broad slate of new and upgraded junior core courses in each major; (c) a new junior core course for both majors on design fundamentals; (d) an upgraded senior core course for both majors on capstone design; and (e) a new design facility dedicated to these junior and senior design studies. Our 2021-22 academic year graduates are the first to emerge entirely from these new programs and are finding outstanding opportunities as entry-level engineers or graduate students. Meanwhile, research, scholarship, and graduate studies in our department have dramatically improved in the last several years. We have experienced a major upswing in funding, productivity, doctoral enrollment, and research impact that leads the Swanson School in multiple categories. Several research areas in Pitt ECE have won major accolades and have been recognized among the best in the nation, as highlighted in this newsletter. One major strength is innovation in ECE for medical and health applications, working closely with our university’s renowned school of medicine and medical center. Another is innovation in ECE for space systems and missions, working closely with NASA, DoD, and industry. For example, on December 21, a new system featuring a wealth of innovative space technologies developed by Pitt ECE was launched on SpaceX-24 as part of the DoD/NASA Space Test Program (STP). This system was deployed in early January 2022 on the International Space Station and began its work as a spaceborne research testbed operated from a ground station on Pitt’s campus. In these and other areas of strength, machine learning and other methods in artificial intelligence and autonomy are featured. I hope you enjoy these stories of success over the past year by our students, faculty, and staff. As exciting as the past year has been for our department, we are even more excited about the future. The Pittsburgh region has become a magnet for research and technologies in autonomous vehicles and artificial intelligence, biomedical systems and data analytics, power generation and distribution, space systems and missions, and much more. Pitt ECE is ideally positioned to maximize the many opportunities in these growing fields in our region and far beyond. Sincerely,

Alan D. George, PhD, FIEEE ECE Department Chair, R&H Mickle Endowed Chair, Professor of ECE, and NSF SHREC Center Director 2 | Winter 2022

Curated Curricula

n 2019, the Department of Electrical and Computer Engineering received approval to adopt new curricula for its two undergraduate programs: electrical engineering and computer engineering. The goal of this ambitious idea was to provide greater synergy between the two fields, create more opportunities for hands-on learning, and address the needs of employers who demand that graduates have a greater breadth and depth of knowledge. “Our curricula needs to continually adapt within these evolving fields of engineering,” said Robert Kerestes, assistant professor and director of the electrical engineering program. “The first cohort of students to participate in these reinvented programs are preparing to graduate in the spring, we look forward to seeing how these efforts have influenced their educational experience and engineering careers.” Eli Brock, a senior ECE student and three-time IEEE Power and Energy Society Scholar, is among the inaugural cohort of students. Throughout his undergraduate years, he has performed research at Pitt and also interned with the Pacific Northwest National Labs, where he worked with a building energy simulation group. “During my internship and research experiences, I feel the new curriculum has given me a solid foundation of concepts and skills to draw from,” he said. “I consistently use ideas I learned in some of the courses, and I feel the curriculum hit a good balance between depth and breadth.” In this new chapter of undergraduate ECE at the Swanson School, balance is key. There is a mixture of classroom and lab experiences, including two design courses, to achieve the hands-on education that today’s students desire. “At times it feels very work intensive, but it’s really satisfying to see the finished product,” said Maria Mysliewiec, a senior ECE student currently enrolled in the Junior Design course. “Since the class is very open-ended, it gives you the opportunity to work toward your goals.” The ECE undergraduate directors are encouraged by the students’ progress and eager to see the outcomes of the new curricula. “We have been updating our undergraduate programs for the past four years, now we are seeing the results,” said Samuel Dickerson, assistant professor and director of the computer engineering program. “Our students have exceeded our expectations, applying what they’ve learned to successfully find top-tier jobs and internships across the country.”

Pitt Collaborates with USC on AI Study of Alzheimer’s

eng Huang, ECE’s John A. Jurenko Endowed Professor, will lead the University of Pittsburgh research on a collaborative study awarded to the University of Southern California’s Mark and Mary Stevens Neuroimaging Informatics Institute. The five-year National Institutes of Health (NIH)-funded effort, “Ultrascale Machine Learning to Empower Discovery in Alzheimer’s Disease Biobanks,” known as AI4AD, will develop state-of-the-art artificial intelligence (AI) methods and apply them to giant databases of genetic, imaging and cognitive data collected from AD patients. Forty co-investigators at 11 research centers will team up to leverage AI and machine learning to bolster precision diagnostics, prognosis and the development of new treatments for AD. “Our team of experts in computer science, genetics, neuroscience and imaging sciences will create algorithms that analyze data at a previously impossible scale,” says Paul Thompson, associate director of the USC INI and project leader for the new grant. “Collectively, this will enable the discovery of new features in the genome that influence the biological processes involved in Alzheimer’s disease.”

Connecting the Dots ... continued from page 1

n collaboration with the University of Illinois at Chicago (UIC), Zhan will couple his CAREER award with two R01 grants from the National Institutes of Health to further investigate brain function in neurological disorders. Maintaining essential brain function, such as learning and memory, requires synapses to pass electrical and chemical signals between neurons. Synaptic dysfunction is a hallmark of many neurological disorders – including Alzheimer’s disease – and leads to hyperexcitation in neuronal circuits. However, neural network changes related to normal aging make it difficult for researchers to distinguish disease-specific alterations from normal changes. Zhan and collaborators will develop innovative computational tools to characterize hyperexcitation patterns in aging and Alzheimer’s Disease and validate their framework with longitudinal mouse models and human data from the Alzheimer’s Disease Neuroimaging Initiative and the Human Connectome Project.

“Current analytic methods have not kept pace with the vast amount and high complexity of data that is being collected on Alzheimer’s disease,” said Huang, who also holds an appointment in the Department of Biomedical Informatics at Pitt. “As a pioneer scientist with more than 15 years of experience in machine learning and biomedical data science, I am the main leader of the advanced AI and machine learning techniques developed in this project.”

“The brain needs to have a balance between neural excitation and inhibition,” said Zhan. “The synaptic dysfunction in Alzheimer’s disease leads to hyperexcitation in neuronal circuits, and this abnormal balance may contribute to disease onset and progression. The hyperexcitation indicator (HI), defined using multimodal MRI data, will signal an imbalance between neural excitation and inhibition.”

His award is in collaboration with Associate Professor Liang Zhan. The joint project has six dedicated core teams that will focus on ultra-scale genomics, imaging, and cognitive data analysis. The Pitt team will lead the AI&ML core and the Genomic Sequencing Data Analysis core while also contributing to the Imaging Genetics core.

Zhan will collaborate on another R01 at UIC to examine late-life depression and uncover its impact on neurodegeneration. They will apply a similar approach to this study and clarify the relationship between depression and neurodegenerative processes in late life. Winter 2022 | 3

Swanson School Space Computing Team Heads to Houston

team of students and their faculty leads recently delivered their newest space system to NASA for launch at the NASA Kennedy Space Center on SpaceX-24 this fall. The system of innovative new computers and sensors, uniquely designed for space and dubbed the Configurable and Autonomous Sensor Processing Research or CASPR system, is part of the U.S. Department of Defense’s Space Test Program (STP), which provides an opportunity to perform cutting-edge technology research on the International Space Station (ISS). The students and faculty are members of the NSF Center for Space, High-performance, and Resilient Computing (SHREC) headquartered at Pitt. SHREC is a national research center sponsored by the National Science Foundation and dedicated to assisting U.S. industrial partners, government agencies, and research organizations in mission-critical computing. Both SHREC and the CASPR mission are led by Dr. Alan George, Mickle Chair Professor and Department Chair of ECE. “SHREC provides Pitt students with the unique opportunity to work with dozens of leading space agencies and companies while earning their engineering degrees,” said Dr. George. “CASPR is the third space system and mission led and developed by SHREC students and faculty, and it represents one of the most advanced space systems ever developed by students and faculty at any university.”

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Observing Earth from Afar As part of their recent delivery to NASA, the SHREC team added two new types of space sensors that will be used to get a better view of Earth and its surroundings. The sensors include a high-resolution binocular telescopic imager, developed by SHREC collaborator Satlantis, and a neuromorphic event-based camera, developed by Prophesee and created by Dr. Ryad Benosman, professor of ophthalmology and ECE at Pitt. “This binocular telescope will point to Earth, and its ground-resolved distance (GRD) will enable us to see things like cars, roads, or trees from the ISS,” said Roffe, who is project

manager of STP-H7-CASPR. “There are other telescopes with this level of GRD, but this one is small – roughly the size of a toaster oven.” With this hardware and an algorithm from Satlantis, they hope to get more detailed images of Earth’s coastlines and other areas of interest for researchers. Unlike the binocular telescope, the neuromorphic sensor will face the horizon, in the direction that the ISS is moving. The device emulates the human retina and will be used to track fast-moving objects in space and improve situational awareness. “When you take a photo with a normal camera, you take a frame, capturing everything in a field of view,” Roffe explained.

Astrobotic and SHREC Partnering for Space Technologies Research

A “This camera is special because it only captures events by looking for changing light intensity in each pixel, which makes it really good at tracking motion.” Let’s say that you used this technology to take a picture of someone walking. The resulting image would only reveal the person in motion, omitting the static background. This device could ultimately help mitigate collisions or assist in docking to the ISS.

Leveling Up Computing Power Performing research on the ISS requires small yet robust tools that are equipped to handle space’s harsh environment. In addition to new sensors, the CASPR system also includes a pair of new high-performance computers for space, each known as a SHREC Space Processor (SSP), which is built to withstand these challenging conditions and perform better than its predecessors from SHREC. “With SSP, the SHREC team has created one of the most innovative, powerful, dependable, and adaptable types of space computers in the world, and our space computers have been adopted by groups across the country for a growing list of recent and upcoming space missions,” said Dr. George.

“The SSP features a unique mix of fixed and reconfigurable electronics, as well as a hybrid combination of commercial and radiation-hardened technologies, resulting in a system that is very powerful, versatile, and resilient and yet very small in size, weight, power, and cost.” The computing system will also test a commercial GPU, or graphics processing unit, to evaluate how it performs in space. GPUs are more powerful than their CPU counterparts for some applications, which for example would allow modern satellites to perform machine learning or improve graphics rendering in space. “This project is really cool because GPUs haven’t flown very often, so it is really leading edge, and our team is doing great work adding resilience to machine learning,” Roffe added. “The area of a GPU that is vulnerable to radiation is much larger than that of a CPU, so we’re excited to see what happens.” In addition to Roffe, the project leads for the CASPR system include the following graduate students: Noah Perryman, Theodore Schwarz, Antony Gillette, Evan Gretok, Tyler Garrett, Sebastian Sabogal, and Thomas Cook.

strobotic and SHREC are pleased to announce a partnership to develop new software and hardware technologies for future space applications. The SHREC consortium, led by Pitt, is an NSF Industry-University Cooperative Research Center (IUCRC) and will work together with Astrobotic by pairing first-class academic researchers with engineering teams to translate concepts into tangible innovations that will support lunar landings, rover missions, satellite servicing, and more. A diverse cohort of researchers, scientists, and engineers at Astrobotic and SHREC will share intellectual property, domain expertise, and practical know-how to develop space computing platforms, among other technologies. Astrobotic and SHREC, both founded in 2007, are examples of the Pittsburgh region’s renewed invigoration in the space industry – Astrobotic with its recent $199.5 million VIPER contract win from NASA and SHREC curating its dozens of partnerships with leading space companies and agencies across the nation. Both Astrobotic and SHREC are participants in the PGH Space Collaborative, a group seeking to coalesce a broader network of existing regional assets to revitalize Pittsburgh as a space robotics hub. The Astrobotic-SHREC partnership begins with a two-year-long agreement and will culminate in an enhanced UltraNav system in 2022.

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Studying RISC-V Architecture to Create Customized Systems for Space Computing

hen choosing a processor for space computing, there are many factors that come into play: because of the rigors of a harsh environment, developers must find the optimal balance between size, weight, power and cost. An important variable in this design is the processor architecture, which can have a significant impact on balancing performance and power consumption. SHREC students examined the RISC-V architecture for space computing and presented their results at the 2021 IEEE Space Computing Conference. They were awarded the Best Paper Award for Research in Space Computing for their work. “RISC-V is exciting because it’s open-source and benefits from collaborative development,” said Michael Cannizzaro, lead author on the paper

and an electrical and computer engineering PhD student. “There is a large community, ranging from individuals to large companies, that are contributing to this development.” RISC – or Reduced Instruction Set Computer – is a more efficient approach to computing that uses a simple, optimized set of instructions compared to other architectures. RISC-V, in particular, is lauded for its modularity – a unique characteristic

that sets it apart from other designs and allows users to add specialized functionality to individual systems. “With RISC-V, the base set of instructions essentially acts as a foundation on which a processor designer can easily develop a system that includes all the features they want, without any unnecessary extras,” Cannizzaro explained. continued on page 13

Pitt Students Invent Canal Battery Guard, a Novel Way to Keep Your Phone Battery Alive Longer

hen Mohamed Morsy (ECE ‘20), Nick Kshatri and Matt Rosenblatt started a first-year engineering class at Pitt called The Art of Making, they had no idea that four years later, they’d still be working together.

The problem they hoped to solve: The more you charge your phone, the weaker the battery becomes. “It was an idea I had prior to taking this class,” says Morsy. “Battery life is always a big issue for a cell phone. Everyone I know has faced this problem with their phone at some point.” What if there was a better way? That question led to the trio’s creation of the Canal Battery Guard, which aims to preserve your phone’s battery, extending the lifespan of your phone. Where most smartphone manufacturers are adding ways to speed up charging, the Canal Battery Guard takes the opposite approach: slowing down charging overnight to give the battery periods of rest. The Canal Electronics team won $5,000 in Pitt’s Randall Family Big Idea Competition which has helped get the fledgling company off the ground. 6 | Winter 2022

Author: Michael Machosky. Originally posted in NextPittsburgh.

Pitt Undergrads Take on the World for a $1 Million Prize at the Indianapolis Autonomous Challenge

ot only was she the lone woman captain of nine remaining university teams competing from across the globe, but Nayana Suvarna was also the youngest at 22, an undergraduate in a field clogged with PhDs and professional autonomous-car racers. Oh, and she was also probably the only one without a driver’s license. One certainly isn’t mandatory to steer a driverless vehicle in the Indy Autonomous Challenge. It took place October 23 at the famed Indianapolis Motor Speedway, home of the Indy 500, and put $1.5 million in prizes up for grabs, with $1 million going to the first place team. Suvarna and her 20 University of Pittsburgh student teammates – joining forces with MIT, Rochester Institute of Technology and the University of Waterloo in Canada – raced as the sole undergraduatesbased team. They’re true underdogs, competing to power their driverless Indy Lights-style vehicle, one rung below the 200-mph Indy Cars that fly around the famed 2.5-mile track known as The Brickyard.

“We placed fourth out of 16 teams” in a May simulation competition, said Suvarna before the race. Suvarna is expected to graduate in December in computer engineering. “We’re hoping to keep up those odds and hopefully podium next Saturday. Hopefully, win first place and a million dollars.” The only pressure was in those fat Indy Light car tires, right? Not so fast, said the team’s advisor. “The whole global autonomous community will be watching, and they’ll be watching University of Pittsburgh Swanson School of Engineering undergraduates competing against professionals,” said Sam Dickerson, associate professor of electrical and computer engineering. “This is an historic race. We’re fortunate in Pittsburgh, seeing autonomous vehicles is an everyday event here.” But nobody has seen anything like this competition. Author: Chuck Finder, University Communications. Originally posted in Pittwire.

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Machine Learning at the Speed of Light

s we enter the next chapter of the digital age, data traffic continues to grow exponentially. To further enhance artificial intelligence and machine learning, computers will need the ability to process vast amounts of data as quickly and as efficiently as possible.

the University of Münster. “This is much faster than conventional chips which rely on electronic data transfer, such as graphic cards or specialised hardware like TPUs (Tensor Processing Unit).”

Conventional computing methods are not up to the task, but in looking for a solution, researchers have seen the light – literally.

The research was conducted by an international team of researchers, including Pitt, the University of Münster in Germany, the Universities of Oxford and Exeter in England, the École Polytechnique Fédérale (EPFL) in Lausanne, Switzerland, and the IBM Research Laboratory in Zurich.

Light-based processors, called photonic processors, enable computers to complete complex calculations at incredible speeds. New research published this week in the journal Nature examines the potential of photonic processors for artificial intelligence applications. The results demonstrate for the first time that these devices can process information rapidly and in parallel, something that today’s electronic chips cannot do.

The researchers combined phase-change materials – the storage material used, for example, on DVDs – and photonic structures to store data in a nonvolatile manner without requiring a continual energy supply. This study is also the first to combine these optical memory cells with a chip-based frequency comb as a light source, which is what allowed them to calculate on 16 different wavelengths simultaneously.

“Neural networks ‘learn’ by taking in huge sets of data and recognizing patterns through a series of algorithms,” explained Assistant Professor Nathan Youngblood and co-lead author. “This new processor would allow it to run multiple calculations at the same time, using different optical wavelengths for each calculation. The challenge we wanted to address is integration: How can we do computations using light in a way that’s scalable and efficient?”

In the paper, the researchers used the technology to create a convolutional neural network that would recognize handwritten numbers. They found that the method granted never-before-seen data rates and computing densities.

The fast, efficient processing the researchers sought is ideal for applications like self-driving vehicles, which need to process the data they sense from multiple inputs as quickly as possible. Photonic processors can also support applications in cloud computing, medical imaging, and more. “Light-based processors for speeding up tasks in the field of machine learning enable complex mathematical tasks to be processed at high speeds and throughputs,” said senior co-author Wolfram Pernice at 8 | Winter 2022

“The convolutional operation between input data and one or more filters – which can be a highlighting of edges in a photo, for example – can be transferred very well to our matrix architecture,” said Johannes Feldmann, graduate student at the University of Münster and lead author of the study. “Exploiting light for signal transference enables the processor to perform parallel data processing through wavelength multiplexing, which leads to a higher computing density and many matrix multiplications being carried out in just one timestep. In contrast to traditional electronics, which usually work in the low GHz range, optical modulation speeds can be achieved with speeds up to the 50 to 100 GHz range.”

Powering AI in Sensors with Energy Harvested from Nature

n a city with 446 bridges, how do you effectively monitor the health of the structures that help residents navigate above Pittsburgh’s three rivers?

Experts rely on remote sensors fastened beneath a bridge that continuously detect vibrations and produce data for structural health monitoring. These kinds of wireless, battery-operated devices are often placed in hard-to-reach areas, complicating maintenance. Researchers from Pitt and Notre Dame want to apply artificial intelligence to extend the lifetime of sensors and devices deployed in remote areas, and they received a $500,000 award from the National Science Foundation to support their work. “One of the major challenges with these sensors is battery replacement. Many times, it is costly, inconvenient, or even infeasible to replace or charge these batteries after deployment,” said Jingtong Hu, lead researcher on the study and associate professor at Pitt. Hu and the research team want to develop a way to save power on the remote sensor device by leveraging energy-harvesting technology, which sources power from the environment, such as solar, thermal, or wind. They plan to add a second, small sensor that can trigger a more robust device, thus saving energy and allowing users to change the battery less frequently. The smaller sensor – powered by energy

harvested from the environment – will run unattended, and with the help of AI, it can be trained to recognize patterns and signal the larger device to turn on during a specific event. “The main device is programmed to do all of the legwork,” explained Hu. “The smaller sensor is the watchdog that can monitor the environment and wake up the larger sensor when necessary.” These devices have many applications, including monitoring and predicting natural disasters. Sensor technology is currently used to observe gases emitted by active volcanoes in some of the most remote parts of the planet. This requires researchers to take long, arduous hikes to reach the location – all while wearing protective equipment to prevent damage to the skin and lungs from the extreme heat and corrosive gases. With Hu’s improvements, the researchers may be able to make trips such as these – whether to the tops of volcanoes or under bridge trusses – less frequently. If successful, the project may ultimately allow these devices to be powered by the environment to help protect the environment. “One of the main challenges of running AI algorithms with energy harvested from the environment is that the energy from the environment is intermittent,” Hu explained. “Much like a laptop, if the sensor loses power, you lose the data, so we want to help AI algorithms reach an accurate decision, even with intermittent power. “By applying AI, we hope to increase the lifespan of unattended sensors and make them more reliable and useful,” he said.

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Designing a More Sustainable

Electric Vehicle T

he global market for electric vehicles (EVs) is expected to grow by more than 25 percent by 2030, with some politicians and manufacturers alike calling for a phase-out of gasoline-powered vehicles by 2035. The White House is even expected to ask automakers to commit to at least 40 percent of their new vehicle sales being electric by the year 2030. However, most electric motors for electric vehicles rely on permanent magnets made with rare-earth metals, which are – as the name implies – a limited resource. To meet the needs of a growing market, designing electric motors without rare-earth metals is a crucial step, especially for sustainable supply chains. Researchers at the Swanson School of Engineering are working with Powdermet Inc., a nanomaterials and advanced materials research and development company in Euclid, Ohio, to develop such an alternative. The Powdermet-led project hopes to create an electric machine that uses permanent magnets made of more abundant metals instead of rare-earth metals. The project recently received $200,000 in funding from the U.S. Department of Energy (DOE) that will allow Powdermet to commercialize MnBi-based permanent magnetic materials developed at the U.S. Department of Energy Ames Laboratory Critical Materials Institute (CMI). At Pitt, this work will be led by Brandon Grainger, Eaton Faculty Fellow and assistant professor of

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electrical and computer engineering, and Paul Ohodnicki, associate professor of mechanical engineering and materials science. Together, the Pitt team will use ANSYS MotorCAD to benchmark an electric motor design that takes advantage of the novel magnetic materials. Powdermet is an industry participant of the Advanced Magnetics for Power & Energy Development (AMPED) Consortium, a research consortium led by director Ohodnicki and codirector Grainger at the University of Pittsburgh. AMPED includes several schools at Pitt, Carnegie Mellon University, North Carolina State University, national labs, and industry partners, bringing together an interdisciplinary skillset well-suited to the research and development of magnetic materials for power electronics and power conversion systems. “AMPED’s mission is both to prepare the next generation of multidisciplinary researchers to innovate with soft magnetics materials in future power conversion systems and to help our partners in industry develop and test the innovations that the world needs now,” said Grainger, who is also associate director of the Energy GRID Institute. “This partnership with Powdermet is a great example of the kind of foundational research and development work we can do when we collaborate with our partners from various engineering disciplines, and we’re excited by the potential impact on the future of EVs.”

Brandon Grainger

Paul Ohodnicki

Research on New Magnetic Materials gets

AMPED Up

s society continues to grapple with the realities of climate change, it looks toward electric vehicles and renewable energy as technological solutions. With these growing technologies, however, there is a greater need for improved soft magnetic materials that can operate in these systems. Meeting this need requires an interdisciplinary skillset, including materials science, applied physics, and electrical engineering, as well as collaboration with end-users in industry. A new consortium created to address this gap, focused on the research and development of magnetic materials for power electronics systems, has received $60,000 in funding from a University of Pittsburgh Momentum Funds Teaming Grant. The consortium, Advanced Magnetics for Power and Energy Development (AMPED), will include members from several schools at Pitt, as well as North Carolina State University and Carnegie Mellon University. “There’s been a historical gap in research and development funding to support these quickly emerging areas, both with new and established industries in the electric power sector,” said Brandon Grainger, Eaton Faculty Fellow and assistant professor. “Our hope is that with this funding, we can invest in the relationships and innovation spaces needed to fill that gap.” Grainger, who is also associate director of the Energy GRID Institute and co-director of AMPED, is leading the effort to establish AMPED at the University of Pittsburgh with Paul Ohodnicki, associate professor of mechanical engineering and material science and director of AMPED. Faculty leadership of the consortium also includes Director Michael McHenry and Co-Director Maarten DeBoer from Carnegie Mellon University, as well as Director Subhashish Bhattacharya and Co-Director Richard Beddingfield from North Carolina State University.

Building a Foundation for High-power Tech

s electrification advancement accelerates and more renewables are integrated into the electric grid, improved power electronics systems are needed to convert AC or DC power into a usable form. New semiconductor device materials and advanced magnetic materials can enable an unprecedented combination of voltage levels and power handling capabilities. However, the latest class of new switching devices, which use so-called ultra-wide bandgap (UWBG) semiconductor materials, will also require improved soft magnetic materials and manufacturing approaches not currently available. University of Pittsburgh researchers Paul Ohodnicki, Brandon Grainger and Ahmed Talaat are working to solve that problem with new materials and manufacturing processes that will establish a foundation for UWBG semiconductors in novel power electronics switching devices. Their investigation received $820,000 in funding from the U.S. Office of Naval Research to support graduate students to explore new ideas in magnetic materials, advanced manufacturing, and advanced component design methods and techniques. The four-year project will address the need for advanced ultrahigh frequency soft magnetics and focus on creation of new ferrite-based systems, advanced manufacturing of components for optimal performance, and the design of optimized transformer and inductor components. The work will also demonstrate enhanced design and optimization tools for inductors. “Emerging ultra-wide bandgap semiconductor materials have enormous potential for high-power applications, but there needs to be a pathway for the magnetic material and component design first,” said Grainger. “Our project will establish the fundamental research necessary to make that happen.”

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Snails Carrying the World’s Smallest Computer Help Solve Mass Extinction Survivor Mystery

ore than 50 species of tree snail in the South Pacific Society Islands were wiped out following the introduction of an alien predatory snail in the 1970s, but the white-shelled Partula hyalina survived. Now, thanks to a collaboration between biologists and engineers with the world’s smallest computer, scientists understand why: P. hyalina can tolerate more sunlight than its predator, so it was able to persist in sunlit forest edge habitats. “We were able to get data that nobody had been able to obtain,” said David Blaauw, the Kensall D. Wise Collegiate Professor of Electrical Engineering and Computer Science at the University of Michigan. “And that’s because we had a tiny computing system that was small enough to stick on a snail.” Most ecology and conservation studies involving data from sensors are done on vertebrate animals,

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which can carry larger and heavier devices than invertebrates. The current study not only offers insights into the conservation measures needed to ensure the survival of a species of snails, it points the way for future studies of very small animals through similar partnerships. “A lot of the coolest scientific work is done at the interface, where you have a classic problem and need to bring new approaches to find a solution,” said Diarmaid Ó Foighil, professor of Ecology and Evolutionary Biology (EEB) at the University of Michigan and Curator of the U-M Museum of Zoology.

The World’s Smallest Computer The Michigan Micro Mote (M3), considered the world’s smallest complete computer, was announced in 2014 by a team Blaauw co-led. This was its first field application.

Inhee Lee, assistant professor of electrical and computer engineering at the Swanson School of Engineering, helped to develop the M3 while earning his PhD at the University of Michigan. Lee was able to adapt the sensor for the biologists’ purposes, helping to solve the mystery of the snails’ survival. The sensor needed to be able to determine whether their white shells gave these snails an evolutionary advantage by tracking light. Since the sensor could already recharge its own batteries with solar cells, Lee realized he could continuously measure the light level by measuring the speed at which the battery was charging. “It was important to understand what the biologists were thinking and what they needed. We already had a tiny sensor design, but we needed to change the sensors to detect light,” explained Lee. “Since the sensor could already

recharge its own batteries with solar cells, we can continuously measure the light level by measuring the speed at which the battery is charging.” “The sensing computers are helping us understand how to protect endemic species on islands,” said Cindy Bick, who received a PhD in ecology and evolutionary biology from U-M in 2018. “If we are able to map and protect these habitats through appropriate conservation measures, we can figure out ways to ensure the survival of the species.” The team glued the sensors directly to the rosy wolf snails, but P. hyalina is a protected species and required an indirect approach. They are nocturnal, typically sleeping during the day while attached underneath leaves. Using magnets, the team placed M3s both on the tops and undersides of leaves harboring the resting P. hyalina. At the end of each day, Lee wirelessly downloaded the data from each of the M3s. The data revealed a dramatic difference in how much sun reached the habitats of the surviving P. hyalina as opposed to the rosy wolf snail. During the noon hour, the P. hyalina habitat received on average 10 times more sunlight than the rosy wolf snails. The researchers suspect that the rosy wolf doesn’t venture far enough into the forest edge to catch P. hyalina, even under cover of darkness, because they wouldn’t be able to escape to shade before the sun became too hot. The research is published by Communications Biology in “Millimeter-sized smart sensors reveal that a solar refuge protects tree snail Partula hyalina from extirpation,” by Cindy Bick, Inhee Lee, Trevor Coote, Amanda Haponski, David Blaauw and Diarmaid Ó Foighil.

Bringing Light into Computers to Accelerate AI and Machine Learning

rtificial intelligence is everywhere, working in the background of a lot of the technology we’ve come to rely on. Nathan Youngblood, assistant professor, has been working on a way to use light-based computing to make the process of machine learning quicker and more efficient. That work will be integral to a new project led by the University of Washington, which recently received $1.2 million over four years from the National Science Foundation to develop a new type of computer chip that uses laser light for AI and machine learning computation. “This hybrid accelerator is a very exciting and powerful extension of our group’s recent work which demonstrated high-speed in-memory computing using a photonic tensor core,” said Youngblood. “Working with our colleagues at UW, we now have the ability to integrate all the electronic and photonic control circuitry that used to fill a lab onto a single computer chip. This will not only reduce the cost of photonic computing, but will also dramatically improve the scalability and efficiency of our photonic AI accelerator.”

Studying RISC-V Architecture ... continued from page 6 Typical architectures are proprietary and require licensing, but RISC-V’s open-source structure decreases development costs and allows a wider audience of innovators to explore its applications. According to the SHREC team, RISC-V may be particularly appealing for space missions. “The architecture’s modularity means that different implementations of RISC-V can be used in a variety of space systems – from navigation and image processing to communications and machine learning,” said Evan Gretok, an electrical and computer engineering PhD student at Pitt, who also contributed to the study. “However, no one can benefit from these features if the

architecture itself can’t perform computations in time and within the strict power consumption constraints of space – that’s where our work comes in.” This research is the starting point of a more in-depth investigation into a promising new architecture that may potentially lead to a spaceready RISC-V computer. “We are currently working on extending this work by incorporating additional architectures, processing platforms, and benchmark tests,” Cannizzaro added. “These new additions will help us make the best conclusions about the RISC-V architecture and its readiness for space.

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AWARDS HONORS Faculty

Students

Heng Huang, the John A. Jurenko Endowed Professor of Electrical and Computer Engineering, has been named a Senior Scholar in this year’s Chancellor’s Distinguished Research Awards. The Award honors faculty members who have an outstanding record of research and academic achievement. The selection committee noted that they were impressed by Huang’s “exceptional contributions to machine learning, artificial intelligence and biomedical data science, which have made an impact on a national and international scale and have a wide range of industrial applications.”

The IEEE Educational Activities Board selected Sabrina Helbig to receive the 2021 Charles LeGeyt Fortescue Graduate Scholarship, and Nate Carnovale received the 2020 scholarship. The award is given to a beginning graduate student for one year of full-time graduate work in electrical engineering.

Brandon Grainger, assistant professor and Eaton Faculty Fellow of electrical and computer engineering, was elected to the board of the EMerge Alliance and will serve as scientific advisor. Established in 2008, the EMerge Alliance works to promote the greater use of DC and hybrid AC/DC microgrids and power systems. The organization has a network of members across a variety of industries that influence the design, construction and management of facilities and properties.

Eli Brock

14 | Winter 2022

Sabrina Helbig

The Institute of Electrical and Electronics Engineers (IEEE) Power and Energy Society (PES) selected Eli Brock, Sabrina Helbig, Anthony Popovski, and Maurice Sturdivant II for its 2020-21 Scholarship Plus Award. The award recognizes high-achieving undergraduate electrical engineering students from across the nation, and over the last nine years, the Swanson School has consistently produced scholars in the program. Two of this year’s recipients – Brock and Popovski – are repeat scholars from the 2019-20 award program. The Pitt Society of Astronautics and Rocketry (SOAR) team was named a finalist in NASA’s 2021 Revolutionary Aerospace Systems Concepts – Academic Linkage (RASC-AL) Special Edition: Moon to Mars Ice & Prospecting Challenge. They traveled to the NASA Langley Research Center in Hampton, VA and won awards for the lightest system mass and most innovative concept. Sushmit Acharya (EE), Caira Borchers (EE), and Zachary Colimon (CoE) were on the winning team.

Anthony Popovski

Maurice Sturdivant II

New Faculty

Azime Can-Cimino

Kara Bocan

Peipei Zhou

Rajkumar Kubendran

Can-Cimino received a BS and MS degree in electrical and electronics engineering from the University of Istanbul, Turkey, and a PhD degree in electrical engineering from the University of Pittsburgh. Prior to Pitt, she worked as a senior software engineer at Emerson Automations Solutions development team, where among other things, she developed AI algorithms for the power and water industry. Her research interests are in machine learning, optimization, and statistics. She has also contributed to other areas including sampling (signal processing), wavelets and compressive sensing.

Bocan received her PhD in electrical engineering from the University of Pittsburgh in 2017, where she also received her BSE in electrical engineering and bioengineering with a minor in neuroscience in 2012. She performed her dissertation research on wireless implantable medical devices with the RFID Center of Excellence, where her use of computer-aided design was an entry point to the field of computational modeling. More recently, her research has focused on the use of computational modeling to enhance understanding of complex systems, and on the development of effective and usable modeling software.

Zhou received her PhD in computer science in August 2019 from the University of California, Los Angeles, where she also received an MS in electrical and computer engineering in June 2014. Her undergraduate studies were in electrical engineering at ChienShiung Wu Honors College, Southeast University, China. She is currently a research scientist at Shanghai Enflame Technology, an AI chip start-up with a research focus on domain-specific language and compiler for AI ASIC Accelerator and computer architecture modeling and system optimization with autotuning.

Kubendran received his PhD degree from the University of California San Diego, where he worked on energy-efficient Neuromorphic VLSI Computing Systems, spanning from devices to applications. His academic interests include low power analog and mixed signal circuit design with emerging non-volatile memory devices to build event-driven architectures for computer vision and machine learning applications. He has demonstrated prototypes of dynamic vision sensors (DVS) and in-memory compute architectures with some of the best energy-efficiency metrics reported in literature. He received an MS degree in electrical and computer engineering from Purdue University in 2012. He received the Best Student Paper award at ISCAS 2013. He has interned with multiple analog and RF design teams in industry, including Intel, IMEC Belgium, MaxLinear and Qualcomm.

She has taught courses part-time as a visiting research assistant professor for the Swanson School’s Department of Electrical and Computer Engineering since Fall 2018, focusing on active learning and student engagement through interactive examples and openended engineering questions. Her teaching interests include blended learning, flipped classrooms, gameful design, technology ethics, and accessibility.

Zhou’s research interests lie in design automation and compilers as well as modeling and optimization for customized, parallel and distributed computing at multiple levels, including chip-level, nodelevel and cluster-level. Her research advances field-programmable gate array-based reconfigurable architecture from a performance, energy and cost perspective for deep learning, precision medicine and other big data and machine learning applications.

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Swanson School of Engineering Department of Electrical and Computer Engineering 1238 Benedum Hall 3700 O’Hara Street Pittsburgh PA 15261

engineering.pitt.edu/ece

Supporting Energy Innovation at NETL for More than a Decade

n ongoing collaborative research team comprising NETL and University of Pittsburgh most recently applied a first-of-its-kind distributive sensing method to solid oxide fuel cells (SOFCs) – a promising clean energy technology. For the most recent accomplishment, which was aimed at improving the durability of SOFCs, Professor Kevin Chen, led the Pitt researchers, who leveraged the extensive research laboratories of the University’s Swanson School of Engineering, to fabricate and functionalize the distributed sensors that were then tested and characterized by NETL researchers in their own cutting-edge facilities. “We are extremely grateful for NETL’s incredibly open attitude toward university collaborations,” Chen said. “Our graduate students and faculty are able to tap into NETL’s wide range of research expertise, which has resulted in not only world-class university research, but also highly trained personnel. NETL’s materials, sensor and modeling expertise supports innovation across so many fields, and previous collaborative work with the Lab has helped to produce energy experts that are now advancing the fields of SOFCS, combustion, rare earth elements, renewable energy and many others. For us, since the Lab is just down the road in South Park Township, NETL is a true national treasure right in our neighborhood.”

UNIVERSI T Y OF PI T T SBURGH | SWANSON S C H O O L O F EN G I N EER I N G | E N G I N E E R I N G . P I T T. E D U / E C E