Energy-Efficiency Computation for Edge Devices 

Abstract: As computing technology continues to advance, one of the enduring challenges for engineers has been to enhance computational capabilities while minimizing power consumption. This challenge has become increasingly critical with the rise of the Internet of Things (IoT), edge computing, and smart devices, where resources are inherently constrained. To enable intelligent edge devices that can operate efficiently in such environments, energy efficiency has emerged as a paramount concern. Addressing this challenge requires the development of novel computing architectures, circuits, and devices specifically designed for low-power operation. This talk will delve into the innovative computing paradigms being explored in our lab, highlighting the cutting-edge circuits and devices that are paving the way for more energy-efficient computation at the edge. By leveraging these advancements, we aim to push the boundaries of what is possible in resource-constrained, intelligent systems, making them not only more powerful but also more sustainable. 

Bio: Dr. Sahil Shah is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of Maryland, College Park. His research focuses on low-power analog and mixed-signal systems, with an emphasis onenergy-efficient computation, embedded machine learning, and biosensing devices. Dr. Shah’s lab is dedicated to developing innovative integrated circuits for real-time signal processing and bio-monitoring applications. Before joining the University of Maryland, Dr. Shah was a Postdoctoral Associate at the California Institute of Technology, where he worked on designing neural decoders for brain-machine interfaces and investigating energy-efficient neural network architectures. He completed his Ph.D. in Electrical Engineering from the Georgia Institute of Technology, focusing on low-power computation using Field Programmable Analog Arrays (FPAA) for wearable devices. He also holds an M.Sc. in Electrical and Computer Engineering from Arizona State University, where he developed CMOS-based biosensors and flexible electronics. Dr. Shah's publication record includes numerous high-impact papers in top IEEE journals and conferences. He has received several prestigious awards, including the National Science Foundation CAREER Award, the George Corcoran Memorial Award, and the Best Design Award by Analog Devices Inc. at the International Solid-State Circuits Conference (ISSCC). In addition to his research, Dr. Shah is an Associate Editor for IEEE Open Journal of Circuits and Systems and IEEE Transactions on Biomedical Circuits and Systems.