Dr. Sunil Kumar received his B.E. (Electronics Engineering) from National Institute of Technology, Surat (India) in 1988, and the M.E. and Ph.D. degrees in Electrical and Electronics Engineering from the Birla Institute of Technology and Science (BITS) , Pilani (India) in 1993 and 1997, respectively. From 1997 to 2002, Dr. Kumar was a Postdoctoral Researcher in the Integrated Media Systems Center and an Adjunct Faculty in the Electrical Engineering Department at the University of Southern California, Los Angeles. During 2000 to 2002, he also worked as a consultant in industry on video compression standards.
Currently, Dr. Kumar is a Professor and Thomas G. Pine Faculty Fellow in the Electrical and Computer Engineering Department at San Diego State University (SDSU), San Diego, California. Prior to this, he served as an Assistant Professor in the Electrical and Computer Engineering Department at Clarkson University, Potsdam, NY (2002 – 2006). He was a Visiting Professor (in 2014) and ASEE Summer Faculty Fellow (in summer of 2007 and 2008) in the Information Directorate at the Air Force Research Laboratory in Rome, NY, where he conducted research in Airborne and Directional Wireless Networks.
Dr. Kumar is a recipient of the SDSU Alumni Outstanding Faculty Award (2015) and President’s Leadership Fund Award for Faculty Excellence (2012). He is a senior member of IEEE and has published more than 150 research articles in international journals and conferences, 7 books/book chapters, and several U.S. invention disclosures. He serves on the technical program committee of many conferences and has organized special sessions and workshops in various conferences. He has received over $4M in external research funding from the National Science Foundation, U.S. Air Force Research Lab, Department of Energy, California Energy Commission, Cisco, and Sprint Advanced Technology Labs.
Dr. Kumar's research interests include (i) QoS-aware and cross-layer protocols for wireless ad hoc, mesh, airborne, sensor, cognitive radio, and cellular networks, including directional communication and spectrum resource optimization, (ii) Error resilient multimedia compression techniques for wireless transmission, including HEVC, H.264/AVC and JPEG2000, and (iii) applications of machine learning techniques in wireless networks.