Suk-Ju Kang
Scholar

Suk-Ju Kang

Google Scholar ID: 3WYxpuYAAAAJ
Sogang University
Image processingvideo processingmultimedia signal processingcircuit design for display and multimedia systemsdeep learni
Citations & Impact
All-time
Citations
2,177
 
H-index
26
 
i10-index
54
 
Publications
20
 
Co-authors
2
list available
Contact
No contact links provided.
Resume (English only)
Academic Achievements
  • Awarded the Engineering Docent Prize by the Korea Institute of Engineering Education in 2025
  • VDSL received the Special Award at the 2025 Samsung Display Industry-Academia Collaboration Paper Contest
  • Student Moon Seung-Hoon received the Silver Award at the 2025 Samsung Display Industry-Academia Collaboration Paper Contest
  • Students Jung Yun-Sung and Nam Jun-Sik received the Encouragement Paper Award at the 35th KIEE AI Signal Processing Conference 2025
  • Student Lee Jun-Ho was selected as a Presidential Science Graduate Fellow in 2025
  • Alumnus Kim Hyun-Sung’s paper was selected for the 2025 KIEE Haedong Excellent Paper Award
  • Student Lim Young-Jae received the Best Paper Award at the 34th KIEE Signal Processing Joint Conference 2024
  • Paper co-authored with student Park Jun-Ho was accepted as an oral presentation at ECCV 2024
  • Student Yoo Hyun-Woo received the Samsung Electronics Industry-Academia Collaboration Excellent Paper Award in 2024
  • Received the Sogang Rich Engineering Fellow Award and Contribution Award in 2023
  • Multiple papers accepted at top venues including NeurIPS 2025, IEEE Transactions journals, ICCV Workshop 2025, IEEE Robotics and Automation Letters, ECCV Workshop 2024, etc.
Background
  • Head of VDS Lab
  • Research interests include various problems in image/signal processing and hardware implementation
  • Specific research topics: image processing systems, frame interpolation, monocular depth estimation and physical distance measurement, multi-view dynamic scene 3D reconstruction
  • Deep learning-based image enhancement and restoration, anomaly detection systems, multi-modal learning
  • Neuro-symbolic AI and foundation models, time series classification, and embedded systems
Co-authors
2 total