Profile

• Organization

  Penn State University

  
  
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  University / College Faculty

  
  
• Website

  https://sites.psu.edu/sengupta/

  
  
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• Biography

  Dr. Abhronil Sengupta is an Assistant Professor in the School of Electrical Engineering and Computer Science at Penn State University. He is also affiliated with 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 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 45 articles in referred journals and conferences and holds 4 granted/pending US patents. He serves on the Technical Program Committee of Design Automation Conference (DAC 2019), International Symposium on Quality Electronic Design (ISQED 2019) and ACM Great Lakes Symposium on VLSI (GLSVLSI 2019). He has been awarded the IEEE SiPS Best Paper Award (2018), Schmidt Science Fellows Award nominee (2017), Bilsland Dissertation Fellowship (2017), CSPIN Student Presenter Award (2015), Birck Fellowship (2013), the DAAD WISE Fellowship (2012), and his publications have featured as APL Editor’s Picks (2015) and top popular articles in TCAS-I, TCAD, TETCI, JAP and JJAP, among others. His work on spin-device based neuromorphic computing has been highlighted in media by MIT Technology Review, US Department of Defense, American Institute of Physics among others. Dr. Sengupta is a member of  the IEEE Electron Devices Society (EDS) and Circuits and Systems (CAS) Society, the Association for Computing Machinery (ACM) and the American Physical Society (APS).