Integrated Circuits and Systems, Memory-Centric Computing, Analog Mixed-Signal and Digital VLSI, Hardware Accelerator, Alternative Computing, Brain-Inspired and Neuromorphic computing, Machine Learning Hardware, Design Automation
Bongjin received his PhD degree from the University of Minnesota in 2014. After his PhD, he worked on design techniques and methodologies for communication circuits and microarchitectures at Rambus and Stanford University as a senior staff and a postdoctoral research fellow. After working as an assistant professor at Nanyang Technological University in Singapore for three years (from 2017 to 2020), he joined the Department of Electrical and Computer Engineering at UC Santa Barbara.
His research team develops innovative integrated circuits and system solutions using traditional CMOS logic and emerging technologies to solve challenging problems in fundamental science and accelerate computations and communications. Target applications include, but not limited to, artificial intelligence, machine learning, robotics, and alternative computing.
He received the Doctoral Dissertation Fellowship Award at the University of Minnesota and the ISLPED International Low Power Design Contest Award. His research works have been published in peer-reviewed conferences and journals, including the International Solid-State Circuits Conference (ISSCC), VLSI Symposium, Custom Integrated Circuits Conference (CICC), and Journal of Solid-State Circuits (JSSC). He has served on the technical program committee for Design Automation Conference (DAC) and the IEEE Solid-State Circuits Letter (SSC-L) editorial review board.