Professor

HyunJin Kim, Associate Professor, School of Electronics and Electrical Engineering,

Dankook University, 152, Jukjeon-ro, Suji-gu,

Yongin-si, Gyeonggi-do, Republic of Korea (Zip code: 16890)

 

Tel: 82-31-8005-3636

Email: hyunjin2@dankook.ac.kr

Location: #508, 2nd Building of Engineering

 

Short Biography

HyunJin Kim is currently a professor in the School of Electronics and Electrical Engineering of Dankook University, Republic of Korea. He received a Ph.D in Electrical and Electronic Engineering, a master degree (MS) and a bachelor degree (BS) in Electrical Engineering, all from Yonsei University, Republic of Korea.  His research interests have resided in the realm of hardware-friendly AI structure and implementation, approximate computing based on the arithmetic solution for deep neural network implementation, string matching algorithm development, embedded & parallel system, and system-on-chip (SoC) design. At this time, he has great interests in Lightweight Neural Network Implementation and Training, Structure of Processing in Memory, and Applications of Reinforcement Learning and Quantum Computing.

Google Scholar Profile: linked here

ResearchGate Profile: linked here

Technical Biography

HyunJin Kim is an associate professor in the School of Electronics and Electrical Engineering at the Dankook University,  Republic of Korea. He received a PhD in Electrical and Electronics Engineering (2010), a master degree (1999) and a bachelor degree (1997) in Electrical Engineering, all from Yonsei University, the Republic of Korea. He enjoyed his studies as a visiting researcher at the University of California, Irvine. (2018.8~2019.7). He worked as the mixed-signal VLSI circuit designer at Samsung Electromechanics for three years. (2002.02 ~ 2005.01). In addition, He is a senior engineer in the field of flash memory controller project at the Memory Division of Samsung Electronics(2002.02 ~ 2005.01). He worked as a visual basic database programmer in his military service (1998.08~2001.10).

His research interests have resided in the realm of hardware-friendly AI structure and implementation, deep neural network implementation, embedded & parallel system and system-on-chip (SoC) design, in particular, approximate & stochastic computing for neural network implementation methodology, fast string matching system, and energy-aware embedded system. Additionally, he extends his research area based on his research history in analogue and digital VLSI design circuit design. At this time, he has great interests in Lightweight Neural Network Implementation and Training and Application of Reinforcement Learning. Also, he has plans to study Structure of Processing in Memory, Computational Storage, and Quantum Computing.

He has published over about 80 technical articles including 39 international journals and 6 international patents. He currently serves as a vice-president in the Institute of Semiconductor Test of Korea.