Rajkumar Kubendran (Senior Member, IEEE) received the M.S. degree in electrical and computer engineering from Purdue University in 2012 and the Ph.D. degree from the University of California San Diego, with a focus on energy-efficient neuromorphic VLSI computing systems, spanning from devices to applications. He is currently an Assistant Professor with the Department of Electrical and Computer Engineering, University of Pittsburgh. He has demonstrated prototypes of dynamic vision sensors (DVS) and in-memory computing architectures with some of the best energy-efficiency metrics reported in the literature. He has interned with multiple analog and RF design teams in the industry, such as Intel, IMEC Belgium, MaxLinear, and Qualcomm. His research interests include low-power analog and mixed signal circuit design with emerging non-volatile memory devices to build event-driven architectures for computer vision and machine learning applications.