Signal processing faculty
Signal processing
Signal processing takes data detected through sensors as code and processes it into information usable for a specific purpose by humanity or computers. Applications in the field include hearing aids, sensors for autonomous vehicles and automatic transcription software.
Electrical engineering faculty members in the Ira A. Fulton Schools of Engineering at Arizona State University are conducting research in a variety of facets of signal processing, including developing technology to distinguish between speech generated by human voices and artificial intelligence, the use of machine learning to classify images, using neural networks for adaptive sensing and recovery, and more.
Ahmed Alkhateeb
Associate Professor
School of Electrical, Computer and Energy Engineering
Alkhateeb’s research interests are in the broad areas of wireless communications, communication theory, signal processing, machine learning, and applied math.
Visar Berisha
Associate Dean and Professor
Melikian Center
Berisha’s research seeks to develop and apply new machine learning and statistical signal processing tools to better understand and model signal perception.
Daniel Bliss
Professor
School of Electrical, Computer and Energy Engineering
Bliss’ research interests include Information theory, estimation theory, and signal processing with applications to wireless communications, remote sensing, and anticipatory physiology and medicine.
Chaitali Chakrabarti
Professor
School of Electrical, Computer and Energy Engineering
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.
Gautam Dasarathy
Associate Professor
School of Electrical, Computer and Energy Engineering
Dasarathy’s research interests span topics in machine learning, statistics, signal processing and networked systems, and information theory.
Oliver Kosut
Associate Professor
School of Electrical, Computer and Energy Engineering
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.
Ying-Cheng Lai
Regents’ Professor
School of Electrical, Computer and Energy Engineering
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.
Antonia Papandreou-Suppappola
Professor
School of Electrical, Computer and Energy Engineering
Research interests: Statistical and time-varying signal processing, adaptive waveform design, Bayesian nonparametric learning, radar, wireless communications, structural health monitoring, biomedical signal processing
Lalitha Sankar
Professor
School of Electrical, Computer and Energy Engineering
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.
Andreas Spanias
Professor
School of Electrical, Computer and Energy Engineering
Andreas Spanias (IEEE Fellow) is Professor in ECEE and Director of the SenSIP Center (NSF I/UCRC). Research areas include signal & speech processing, sensors & machine learning, Quantum AI and Engineering Education.
Cihan Tepedelenlioglu
Associate Professor
School of Electrical, Computer and Energy Engineering
Tepedelenlioglu’s areas of expertise include wireless communications statistical signal processing estimation and equalization.
Konstantinos Tsakalis
Professor
School of Electrical, Computer and Energy Engineering
Tsakalis’ research interests include control systems, adaptive control, process control and control of semiconductor manufacturing processes, and application of feedback control in epilepsy.
Pavan Turaga
Director and Professor
School of Arts Media and Engineering
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.