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Abhronil Sengupta

Abhronil Sengupta

Based in University Park, PA, United States

Bio:

Dr. Abhronil Sengupta 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 is also affiliated with the Department of Materials Science and Engineering and the Materials Research Institute (MRI).

Dr. Sengupta received the PhD degree in Electrical and Computer Engineering from Purdue University in 2018 and the B.E. degree from Jadavpur University, India in 2013. He worked as a DAAD (German Academic Exchange Service) Fellow at the University of Hamburg, Germany in 2012, and as a graduate research intern at Circuit Research Labs, Intel Labs in 2016 and Facebook Reality Labs in 2017.

The ultimate goal of Dr. Sengupta’s research is to bridge the gap between Nanoelectronics, Neuroscience and Machine Learning. He is pursuing an inter-disciplinary research agenda at the intersection of hardware and software across the stack of sensors, devices, circuits, systems and algorithms for enabling low-power event-driven cognitive intelligence. Dr. Sengupta has published over 95 articles in referred journals and conferences and holds 3 US patents. He serves on the IEEE Circuits and Systems Society Technical Committee on Neural Systems and Applications, Editorial Board of IEEE Transactions on Cognitive and Developmental Systems, Scientific Reports, Neuromorphic Computing and Engineering, Frontiers in Neuroscience journals and the Technical Program Committee of several international conferences like DAC, ICCAD, ISLPED, ISQED, AICAS, ICONS, GLSVLSI, ICEE, SOCC, ISVLSI, MWSCAS and VLSID. He has been awarded the ARO Early Career Award (2024), NSF CAREER Award (2023), IEEE Electron Devices Society (EDS) Early Career Award (2023), IEEE Circuits and Systems Society (CASS) Outstanding Young Author Award (2019), Facebook Faculty Award (2018), IEEE SiPS Best Paper Award (2018), Schmidt Science Fellows Award nominee (2017), Purdue Bilsland Dissertation Fellowship (2017), CSPIN Student Presenter Award (2015), Birck Fellowship from Purdue University (2013), the DAAD WISE Fellowship (2012). His work on neuromorphic computing has been highlighted in media by MIT Technology Review, ZDNet, US Department of Defense, American Institute of Physics, IEEE Spectrum, Nature Materials, among others. Dr. Sengupta is a Senior Member of the IEEE and member of IEEE Electron Devices Society (EDS), IEEE Magnetics Society and IEEE Circuits and Systems (CAS) Society, the Association for Computing Machinery (ACM), the American Physical Society (APS) and the Association for the Advancement of Artificial Intelligence (AAAI). He currently serves as an ACM Distinguished Speaker (2024-2027).

Available Lectures

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Neuromorphic Computing: Bridging the gap between Nanoelectronics, Neuroscience and Machine Learning
While research in designing brain-inspired algorithms have attained a stage where such Artificial Intelligence platforms are being able to outperform humans at several cognitive tasks, an...

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