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.

Berisha’s research seeks to develop and apply new machine learning and statistical signal processing tools to better understand and model signal perception.

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.

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.

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

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, classical and quantum.

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.

Anamitra Pal is an Associate Professor in the School of Electrical Computer and Energy Engineering, where he leads the Phasor Assisted Learning (PAL) Lab: https://faculty.engineering.asu.edu/pal/

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.

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.

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.

Their research in machine learning has resulted in new algorithms for geometrical analysis of feature-spaces which leads to increased robustness in several end-applications.

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.