Accolades

Pramod Khargonekar, vice chancellor for research and Distinguished Professor of electrical engineering and computer science, won the 2019 IEEE Control Systems Award for outstanding contributions to robust and optimal control theory.

His research contributions span systems and control theory and applications, including foundational contributions to robust and H-infinity optimal control theory. His work has had wide-ranging impact on theoretical developments in the field as well as the emergence of computeraided design tools.

Khargonekar also was appointed to the editorial board of the Proceedings of the IEEE, the flagship IEEE journal in the fields of electronics, electrical and computer engineering, and computer science. The publication’s board members are responsible for generating ideas, reviewing manuscripts, helping plan special issues and sections, and offering advice to the editor-in-chief and managing editor. Khargonekar began his three-year term on Jan. 1, 2020.

The IEEE International Conference on Communications awarded Lee Swindlehurst and two colleagues a 2020 Best Paper Award for their work that details using a type of machine learning to improve performance in multi-antenna wireless communication systems.

Swindlehurst, professor of electrical engineering and computer science, collaborated on “SVM-based Channel Estimation and Data Detection for Massive MIMO Systems with OneBit ADCs” with San Diego State professor Duy Nguyen and Ly Van Nugyen, a doctoral student in the UC Irvine/SDSU Joint Program in Computational Science.

The paper describes using a classical method of machine learning called support vector machines to target new 5G-and-beyond systems, which employ large arrays of antennas. These arrangements, called massive MIMO – multi-input, multi-output wireless systems – can be costly and use a lot of power, so researchers seek ways to reduce price and power usage without sacrificing performance. “Our paper shows how to use machine learning and signal processing to reduce the performance loss that results when very low-resolution (one-bit) sampling hardware, referred to as analogto-digital converters, are used in a massive MIMO implementation,” said Swindlehurst.

Filippo Capolino, professor of electrical engineering and computer science, was named a 2020 IEEE Fellow for his contributions to the development of electromagnetic phenomena in metamaterials and periodic structures.

The fellow designation is awarded by the IEEE board of directors to only one-tenth of one percent of the organization’s voting membership – those considered to have extraordinary records of accomplishment.

Capolino’s research interests include metamaterials and their applications, traveling wave tubes, antennas, wireless systems, sensors in both microwave and optical ranges, plasmonics, nano-optics, spectroscopy, microscopy and applied electromagnetics in general.

Michael Green was named interim dean of the Samueli School of

Engineering, July 1, 2020. Green replaces Gregory Washington, who became the president of George Mason University in Virginia.

Green, professor of electrical engineering and computer science, joined the faculty in 1997. He has served in a range of academic leadership positions, including his current role as associate dean for undergraduate studies since 2017 and as department chair from 2009-2014. He also served on the faculty at Stony Brook University and worked as an integrated circuit design engineer at National Semiconductor Corp. and Newport Communications (now part of Broadcom Inc.).

Green earned his doctorate in electrical engineering from UCLA. His current research interests include the design of analog and mixed-signal integrated circuits for use in applications, including high-speed communication networks and biomedical devices. He has published more than 120 papers in technical journals and conferences and has received six patents. Green has been recognized with several teaching and industry honors, including the Award for New Technical Concepts in Electrical Engineering from IEEE Region 1, the Guillemin-Cauer Award of the IEEE Circuits and Systems Society and the IEEE W. R. G. Baker Award.

Hung Cao, assistant professor of electrical engineering and computer science, and biomedical engineering, edited a book, “Interfacing Bioelectronics and Biomedical Sensing,” with colleagues from UC San Diego and UCLA.

Published by Springer Nature, the book examines the fundamental challenges of interfacing bioelectronics with human and animal tissue. It covers topics ranging from retinal implants that restore vision, to implantable circuits for neural biomedical devices, to intravascular electrochemical impedance for detecting unstable plaque deposits in arteries.

“We address several hot topics in the field of biomedical microdevices and systems, such as optimization of electrodetissue interface, wireless power transfer, neural implants, novel biomaterials and high-frequency ultrasound just to name a few,” said Cao, whose NIH- and NSFfunded research involves developing and leveraging novel microdevices and sensors for use in biology and medicine.

The chapter overseen by Cao covers basics about cardiac functions, the use of zebrafish as the premier animal model to study cardiac disease and heart regeneration, as well as the use of artificial intelligence in biological studies, diagnosis and prognosis.

[ACCOLADES]

Mohammad Al Faruque, associate professor of electrical engineering and computer science, published a book, “DataDriven Modeling of Cyber-Physical Systems using Side-Channel Analysis,” with his graduate student Sujit Rokka Chhetri.

Published by Springer Nature, the book covers the use of state-of-theart machine learning and artificial intelligence algorithms for modeling various aspects of cyber-physical systems, provides practical use cases for securing these systems from attacks, and discusses building and maintaining a digital twin of the physical system.

“This is the only book I know of that addresses data-driven modeling of cyber-physical systems and how the approach can be used to model the interactions between the cyber and physical domains of the systems,” said Al Faruque, who conducts research on system-level design of embedded and cyber-physical systems with a special focus on design automation, model-based design, security and embedded machine-learning algorithms.

Present day cyber-physical systems in automotive and manufacturing generate and log large amounts of data. “These multidomain runtime data are rich in information regarding various states of the system like its health, security status, etc.” said Chhetri, who earned a doctorate in 2019 and now works as a staff data scientist at Palo Alto Networks, a cybersecurity company. “This book presents various approaches to take advantage of these data and utilize them for improving the cyber-physical systems, which may otherwise not be possible during design time.”

The Institute of Navigation honored Zak Kassas with its Colonel Thomas L. Thurlow Award for outstanding contributions to the science of

navigation. Kassas, associate professor of mechanical & aerospace engineering and electrical engineering & computer science, was recognized for his work in the theory and practice of exploiting signals of opportunity for accurate and reliable positioning, navigation and timing.

Kassas specializes in analyzing these signals – existing radio signals from cell towers, Wi-Fi and low-Earth-orbit satellites – to map, position and navigate UAVs, ground vehicles and pedestrians in indoor environments with high accuracy, without relying on GPS signals.

The award is named for Thurlow, an engineer and pilot who contributed significantly to the development and testing of navigation equipment and training of navigators and pilots.

Mohammed Alnemari, graduate student in electrical engineering and computer science, won a Best Student Paper award at the 2019 IEEE International Conference on Edge Computing, held in Milan,

Italy, last summer. Alnemari is a second-year doctoral student under the advisement of Nader Bagherzadeh, professor of electrical engineering and computer science.

In his paper, “Efficient Deep Neural Networks for Edge Computing,” Alnemari presented a two-stage pipeline approach, called filter pruning and tensor train decomposition, to reduce the storage and computation requirements of DNNs in order to more easily deploy them on the edge. “Our work demonstrates the same accuracy or just a tiny degradation of accuracy with retraining, after applying both stages,” said Alnemari.

EECS Welcomes New Faculty in Academic Year 2019-2020

Hamidreza Aghasi, Assistant Professor Research Interests: analog circuit design, mm-wave and terahertz integrated circuits, high resolution integrated sensing and imaging, neuromorphic computation, emerging device technologies Education: Ph.D., Cornell University

Salma Elmalaki, Assistant Professor of Teaching Research Interests: mobile computing, pervasive autonomous systems, personalized computing, and internet-of-things (IoT) Education: Ph.D., UCLA

Dr. Terence Sanger, Professor Research Interests: computational neuroscience, machine learning, failure models of biological network computing, robotic models of neurological disorders, dystonia, childhood movement disorders, biological signal processing, adaptive control, stochastic systems Education: Ph.D., MIT; M.D., Harvard Medical School

Yanning Shen, Assistant Professor Research Interests: machine learning, data science, network science and statistical-signal processing Education: Ph.D., University of Minnesota

Yasser Shoukry, Assistant Professor Research Interests: resilience, safety, security and privacy of artificial intelligence (AI), controlled cyberphysical systems (CPS), internet-of-things (IoT), and robotic systems Education: Ph.D., UCLA