Sahil Shah is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of Maryland, College Park. He officially joined the UMD ECE Department in Spring 2021. His area of expertise is low-power analog and mixed-signal systems for energy-efficient computation. His lab investigates and designs low-power systems that can compute efficiently in a low-resource environment, such as implantable or wearable platforms. Prior to his arrival at the University of Maryland, Sahil was a postdoctoral associate in the department of Electrical Engineering at California Institute of Technology. At Caltech, he pursued research on developing robust brain-machine interface for enabling patients to control prosthetic devices. He received his PhD in Electrical Engineering from Georgia Institute of Technology in 2018 where he developed reconfigurable mixed-signal neural networks for monitoring vital and physiological signals. In 2014, he received M.Sc. from Arizona State University for developing CMOS based biosensors for monitoring pH in cell-culture media. His research interests fall into three major areas: Energy-Efficient integrated circuits, Embedded Machine learning, and Bio-Sensing and Monitoring. Sahil's long term goal is to develop robust and energy-efficient devices that will equip physicians with tools to make better diagnosis, tailor rehabilitation process for patients and technology that will help us better understand physiological and neurological activity.
HONORS AND AWARDS
- Analog Devices Inc. Outstanding Student Designer Award (2015)
- Marion A. and Henry C. Bourne fellowship from Georgia Institute of Technology
- Energy-Efficient Integrated Circuits
- Embedded Machine Learning
- Bio-Sensing and Monitoring