Background

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. 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.

Education

• PhD in Electrical Engineering from Georgia Institute of Technology in 2018
• M.Sc. from Arizona State University in 2014

Research Interests

• Energy-Efficient Integrated Circuits
• Embedded Machine Learning
• Bio-Sensing and Monitoring

View recent research projects

Publications

2020

• Jennifer Hasler and Sahil Shah “An SoC FPAA based Programmable, Ladder-Filter Based, Linear-Phase Analog Filter” in IEEE Transactions on Circuits and Systems I: Regular Papers, vol. 68, no. 2, pp. 592-602, Feb. 2021, doi: 10.1109/TCSI.2020.3038360.

​Prior to 2021

• Sahil Shah, Hakan Toreyin, Gungor Cihas, Jennifer Hasler “A Real-Time Vital-Sign Monitoring in the Physical Domain on a Mixed-Signal Reconfigurable Platform” in IEEE Transactions on Biomedical Circuits and Systems, vol. 13, no. 6, pp. 1690-1699, Dec. 2019 doi: 10.1109/TBCAS.2019.2949778.
• Jennifer Hasler and Shah S. “Security Implications for Ultra-Low Power Configurable SoC FPAA Embedded Systems​” J. Low Power Electron. Appl. 2018, 8(2), 17. 5 June 2018.
• Shah S. and Jennifer Hasler “SoC FPAA Hardware Implementation of a VMM+WTA Embedded Learning Classifier” in IEEE Journal on Emerging and Selected Topics in Circuits and Systems, vol. 8, no. 1, pp. 28-37, March 2018.
• Shah S., H. Toreyin, J.Hasler and A. Natarajan “Temperature Sensitivity and Compensation On A Reconfigurable Platform ” in IEEE Transactions on Very Large Scale Integration (VLSI) Systems, vol. 26, no. 3, pp. 604-607, March 2018.(pdf).

Honors and Awards

• Analog Devices Inc. Outstanding Student Designer Award (2015)
• Marion A. and Henry C. Bourne fellowship from Georgia Institute of Technology

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