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Digital and analog Very Large-Scale Integration (VLSI) circuit, architecture, and system for machine learning and signal processing algorithms based on emerging computing paradigms
The VVIP (Vertically-integrated VLSI Information Processing) Lab at UC San Diego, led by Professor Mingu Kang, aims to achieve energy- and latency-efficient VLSI hardware for machine learning and signal processing algorithms across multiple research stacks including circuit and device at the bottom, architecture in the middle, and system and algorithm at the top. This research goal is achieved by leveraging novel computing paradigms including in-memory, in-sensor, and neuromorphic computing.
Mingu Kang joined the Electrical and Computer Engineering Department at the University of California San Diego in 2020 as an Assistant Professor. He received the B.S. and M.S. degrees in Electrical and Electronic Engineering from Yonsei University, Seoul, South Korea, in 2007 and 2009, respectively, and the Ph.D. degree in Electrical and Computer Engineering from the University of Illinois at Urbana–Champaign (UIUC), Urbana, IL, USA, in 2017. Prior to joining UCSD, he was with IBM Thomas J. Watson Research Center, Yorktown Heights, NY, USA, where he worked for machine learning accelerator architectures from 2017 to 2020. He was also with the Memory Division, Samsung Electronics, Hwaseong, South Korea, where he was involved in the circuit and architecture design of phase-change memory from 2009 to 2012.