AI and machine learning faculty

Alkhateeb’s research interests are in the broad areas of wireless communications, communication theory, signal processing, machine learning, and applied math.

I have a joint appointment in engineering and health. My work develops AI tools to track neurological conditions via speech, leading to FDA-registered tools used globally in healthcare.

Bliss’ research interests include Information theory, estimation theory, and signal processing with applications to wireless communications, remote sensing, and anticipatory physiology and medicine.

Chakrabarti’s areas of expertise include low power embedded system design, reliable memory design, VLSI architectures for signal processing and communications, and algorithm-architecture codesign.

Krishnendu Chakrabarty is the Fulton Professor of Microelectronics in the School of Electrical, Computer and Energy Engineering at Arizona State University.

Daphne Chen is an Assistant Professor in the School of Electrical, Computer and Energy Engineering at Arizona State University (ASU), Tempe. She received her Ph.D. in Electrical and Computer Engineering from The University of Texas at Austin, and her B.S. and M.S. degrees from National Chiao Tung University, Taiwan. Prior to joining ASU, she served as an Assistant Professor in the Department of Electrical Engineering at Northern Arizona University. She also held industry positions as an R&D Pathfinding Emerging Memory Engineer at Micron Technology and as a hardware developer at IBM, working on emerging memory and computing applications. Her research…

Vidya A. Chhabria is an assistant professor in ECEE at Arizona State University. Her research interests lie in CAD for VLSI systems around physical design, optimization, and analysis algorithms.

Dasarathy’s research interests span topics in machine learning, statistics, signal processing and networked systems, and information theory.

Fan’s research interests include efficient AI hardware and algorithm, digital chip design, in-memory computing circuits and architecture, adversarial and trustworthy AI system.

Fan’s current research is in the areas of semiconductors and phase-change materials for electronics and photonics such as neuromorphic devices and tunable photonic devices; nanomaterials for electrochemical energy storages.

Dr. Gu received his Ph.D. degrees, under the supervision of Prof. David Z. Pan and Prof. Ray T. Chen, in Electrical and Computer Engineering from The University of Texas at Austin, Austin, TX, USA, in 2023. He has broad research interests spanning from emerging hardware design for efficient computing (photonics, post-CMOS electronics, quantum), hardware-algorithm co-design, efficient AI/ML algorithms, and electronic-photonic design automation.Dr. Gu has authored 80+ peer-reviewed international journal/conference papers in above area. He has received Best Paper Award at ASP-DAC 2020, selected as one out of 6 Best Paper Finalists at DAC 2020, won First Place at the ACM/SIGDA Student Research Competition (SRC) held…

Hedman is a professor in the School of ECEE and is the director of PSERC. In 2017, Hedman received the Presidential Early Career Award for Scientists and Engineers (PECASE), awarded by President Barack H. Obama.

Leslie Hwang is an assistant professor in the School of Electrical, Computer and Energy Engineering. She joined ASU after working at Synopsys as a senior research and development engineer, where she worked on the machine learning team for the company’s IC Validator, which verifies correctness and manufacturability of semiconductor chip designs. Hwang’s awards include an Intel computer engineering fellowship and the University of Illinois Urbana-Champaign’s Harold L. Olesen Undergraduate Teaching Award. Her expertise is in applied machine learning for physical design in electronics and advanced semiconductor packaging.

Jayasuriya’s research focuses on designing new types of computational cameras, systems, and visual computing algorithms. Our lab website can be found here: https://sites.google.com/asu.edu/imaging-lyceum

Karam’s research interests include image/video processing, compression and transmission, computer vision, machine learning, visual quality assessment and perception, multidimensional signal processing, digital filtering and biomedical imaging.

Oliver Kosut is an associate professor in ECEE. His research focuses on information theory, particularly with applications to security, privacy, and machine learning, and smart grid cyber-security.

Lai has been recognized with awards such as White House PECASE, APS fellowship and Pentagon Vannevar Bush Fellowship. He has been publishing in complex dynamical systems and machine learning. Current H-index is 90.

Kexin (Kathy) Li is an assistant professor in the School of Electrical Computer and Energy Engineering. She earned her Ph.D. in Electrical and Computer Engineering from the University of Illinois Urbana-Champaign in 2022 and joined ASU after working as a postdoctoral researcher at Columbia University. Kexin’s research focuses on understanding and modeling the physical behavior of emerging nanoscale electronic materials and devices, to enable new system-level functionalities for high-power and high-frequency applications. Her current work involves building a framework for technology-circuit and device-circuit co-design, which requires expertise in nanoelectronics, semiconductor device physics, and circuit design. Kexin has collaborated extensively with…

Michelusi’s expertise is in resource allocation and optimization of wireless communications systems.

Nedich’s research interests include large-scale distributed systems, sensor networks and network science, data analytics, decision and control systems and operations research.

Duong Nguyen is an Assistant Professor in the School of Electrical, Computer, and Energy Engineering at Arizona State University. He received his doctorate in electrical and computer engineering from the University of British Columbia in 2020, under the supervision of Professor Vijay Bhargava. His research lies at the intersection of operations research, artificial intelligence, economics, and engineering, with a focus on developing new mathematical models and techniques for decision-making and economic analysis of large-scale networked systems such as cloud/edge computing, smart grids, and crowdsourcing. His goals are (1) to design optimal operation and planning algorithms for complex systems under uncertainty,…

Anamitra Pal leads the Phasor Assisted Learning (PAL) Lab at ASU and does research in the areas of power systems data analytics, renewable integration, and critical infrastructure resilience.

Research interests: Statistical and time-varying signal processing, adaptive waveform design, Bayesian nonparametric learning, radar, wireless communications, structural health monitoring, biomedical signal processing

Ramapuram Matavalam’s research addresses the challenges in achieving a 100% green power grid by leveraging machine learning and dynamical system theory.

Reisslein received a doctorate in systems engineering from the University of Pennsylvania in 1998.

Nick’s research group focuses on developing next-generation renewable energy devices—with a focus on printable thin-film photovoltaics and batteries—using high-throughput processing and reliability-based characterization.

Dr. Lalitha Sankar is a Professor in the School of ECEE. Her research interests are at the intersection of information and data sciences with focus on fairness, privacy, and robustness.

Arindam Sanyal is currently an assistant professor in the School of Electrical, Computer and Energy Engineering at Arizona State University. Prior to this, he was an Assistant Professor in the Electrical Engineering Department at University at Buffalo SUNY. He was an analog design engineer with Silicon Laboratories between 2015-2016. He received his PhD in Electrical and Computer Engineering from the University of Texas at Austin in 2015, his M.Tech from The Indian Institute of Technology, Kharagpur in 2009 and B.E from Jadavpur University, India in 2007. His research expertise includes analog/mixed signal integrated circuits design and machine learning.

Shandhi is an assistant professor with a joint appointment in the School of Electrical, Computer, and Energy Engineering and Biodesign Institute Center for Bioelectronics and Biosensors at ASU.

Si’s expertise includes approximate dynamic programming/reinforcement learning, data-driven real-time control of nonlinear dynamic systems, control of robotic prosthesis.

Andreas Spanias (IEEE Fellow & Fulbright US Scholar) is Professor in ECEE and Director of the SenSIP Center (NSF I/UCRC). Research areas include signal & speech processing, sensors & machine learning, and Quantum AI.

Tepedelenlioglu’s areas of expertise include wireless communications statistical signal processing estimation and equalization.

Tsakalis’ research interests include control systems, adaptive control, process control and control of semiconductor manufacturing processes, and application of feedback control in epilepsy.

Tsiropoulou works on game theory and reinforcement learning for decision making in complex systems, with emphasis on network modeling and optimization, resource management, network economics, and Internet of Things.

Pavan Turaga is the Founding Director of The GAME School at ASU (2025), overseeing a transdisciplinary group of faculty and degree programs, spanning gaming, esports, interactive, immersive and AI-enabled media.

Vittal is a Regents Professor and an ASU Foundation Professor in Electric Power Systems. His areas of expertise include electric power, power system dynamics and controls, and nonlinear systems.

Weng’s research interests include power systems, machine learning, demand response, data analytics, cyber-physical systems and convex optimization.

Zhang’s research expertise spans deep learning, computer architecture, embedded systems and VLSI design automation.

Networked system security and privacy, AI and machine learning, wireless networking, and mobile computing.

Zou’s research focuses on fundamental algorithms and theory of machine learning and statistical signal with applications to connected and autonomous systems, health science and power systems.