Sogang University | South Korea
Prof. Suk-Ju Kang is a distinguished Professor in the Department of Electronic Engineering at Sogang University, Seoul, Korea, specializing in visual computing, computer vision, and artificial intelligence. His research spans image synthesis and restoration, real-time 2D/3D human and hand pose estimation, and industrial AI applications such as anomaly detection and remaining useful life prediction. Prior to joining Sogang University in 2015, he served as Assistant Professor at Dong-A University and worked as a Senior Research Engineer at LG Display, contributing to advanced display technologies. He earned his Ph.D. in Electrical Engineering from POSTECH under the supervision of Dr. Young Hwan Kim, and his B.S. in Electronic Engineering from Sogang University. Prof. Kang has authored over 209 peer-reviewed publications, which have collectively garnered over 2,143 citations with an h-index of 25, reflecting his global research impact. He has been recognized with numerous honors, including the 2025 Haedong Best Paper Award, multiple Samsung Best Paper Awards (2023, 2024), the 2022 Merck Young Scientist Award, and the 2020 Young Researcher Award from The Korean Institute of Broadcast and Media Engineers. He also plays an active leadership role in academia, serving as Chairman of the AI and Computational Technology Society for Display, Chairman of the Image Processing Research Society, and Organizing Committee Chair for major international conferences such as ITC-CSCC and AISPC.
Featured Publications
“Luminance Compensation for Stretchable Displays Using Deep Visual Feature-Optimized Gaussian-Weighted Kernels.” Journal of the Society for Information Display, 2025.
“DGTFNet: Depth-Guided Tri-Axial Fusion Network for Efficient Generalizable Stereo Matching.” IEEE Robotics and Automation Letters, 2025.
“CRAN: Compressed Residual Attention Network for Lightweight Single Image Super-Resolution.” IEEE Signal Processing Letters, 2025.
“Supervised Denoising for Extreme Low-Light Raw Videos.” IEEE Transactions on Circuits and Systems for Video Technology, 2025.
“Query-Vector-Focused Recurrent Attention for Remaining Useful Life Prediction.” IEEE Transactions on Reliability, 2025.