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Abhronil Sengupta
"My Purdue Engineering education has been instrumental in my career. Purdue's strong leadership in semiconductors and computing provided me with the perfect background to lead an interdisciplinary research group at the merger of Electrical Engineering and Computer Science. Additionally, I pursued my PhD in Prof. Kaushik Roy's group at Purdue University which provided me access to a cutting-edge research program in the field of brain-inspired computing. My advisor's own visionary leadership in leading a large and diverse research group has shaped by own outlook as a faculty member, researcher and educator."
Abhronil Sengupta | Electrical and Computer Engineering
Joseph and Janice M Monkowski Career Development Professor, Pennsylvania State University
The ultimate goal of Abhronil Sengupta's research is to bridge the gap between nanoelectronics, neuroscience, and
machine learning. To that end, he is pursuing a multi-disciplinary research agenda at the intersection of hardware and
software across the stack of sensors, devices, circuits, systems, and algorithms for providing an end-to-end solution to
enable low-power event-driven cognitive intelligence. He is an associate professor in the School of Electrical
Engineering and Computer Science at Penn State University and holds the Joseph R. and Janice M. Monkowski Career
Development Professorship. He leads an interdisciplinary team driven by a holistic system-science enabled research and
education perspective — ranging from disruptive algorithms to emerging device technologies — addressing
fundamental challenges related to scalability, efficiency and explainability of AI systems.
His research has been sponsored across a spectrum of agencies ranging from materials, devices, computing, brain and
cognitive science related divisions, as well as hardware and software companies. He has published more than 95 articles
in referred journals and conferences and holds three U.S. patents. Within six years of earning his PhD, he received
5,584 citations — with his 2019 work on scalable neuromorphic algorithms considered one of the important
benchmarks in the field (1116 citations).
Sengupta's vast list of awards includes the Army Research Office Early Career Award, NSF CAREER Award, and IEEE Electron
Devices Society Early Career Award for contributions in the field of neuromorphic computing and AI hardware.