Associate Professor, Dept. of Software and Computer Engineering, Ajou University (아주대학교)
Email: jongbinryu at ajou.ac.kr / jongbin.ryu at gmail.com
Research interest: Computer Vision, Efficient LLMs, and Robot Learning
2026 News: 1 CoRL, 1 Applied Energy, 3 EMNLP (main), 1 BMVC paper accepted
Students interested in my lab, please feel free to contact me at any time.
Ph.D. Computer Science, KAIST (Feb 2012 - Feb 2017)
M.S. School of Electrical and Electronics Engineering, Chung-Ang University (Mar 2009 - Feb 2011)
B.S. School of Electrical and Electronics Engineering, Chung-Ang University (Mar 2002 - Feb 2009)
Associate Professor at Ajou University (2024 - Now)
Assistant Professor at Ajou University (2020 - 2024)
Research Fellow at Hanyang University (2017 - 2020)
Lecturer at KAIST IT Academy (2013-2015)
Researcher at Institut Pasteur Korea (2010-2011)
Software Engineer at Siemens Korea Ultrasound Research (2010)
Captin of Korean Martial Arts (Taekwondo) Team at Chung-Ang University (2007-2008)
Military Service at Republic of Korea Army (2005-2007)
Sungeun Kim (Ph.D)
Junhyung Ko (Ph.D)
Hankyul Kang (Ph.D)
Seungmin Oh (Ph.D)
Yuri Kim (Integrated M.S and Ph.D)
Seunghoon Kang (Integrated M.S and Ph.D)
Donghyun Kim (Integrated M.S and Ph.D)
Donggun Lee (Integrated M.S and Ph.D)
Gregor Seifer (M.S)
Dongkyu Kim (M.S)
Kyusung Nam (M.S)
Euihak Heo (M.S)
Eunjoo Shin (M.S)
Duyeon Na (M.S)
Chaeyun Eom (M.S)
Mingyu Jeong (M.S)
Minjae Kim (M.S)
Junhyeong Go, Mingyu Jung, Woobin Im, and Jongbin Ryu, "FlowVLA: Enabling World Dynamics Understanding through Pluggable 3D Flow Learning", Conference on Robot Learning (CoRL) 2026
Sungeun Kim, Mingyu Jung, Yuri Kim, Jin-Sung Park, and Jongbin Ryu "One-Cycle Based Battery Remaining Useful Life Prediction by Continuous Wavelet Scale Compression with Deep Neural Networks", Applied Energy, 2026
Eunju Shin and Jongbin Ryu, "Colla-Q: Toward Collaborative Experts in MoE Quantization via Minimax Precision Balancing", Empirical Methods in Natural Language Processing (EMNLP), 2026
Donggeon Lee, Dooyeon Na, Seungmin Oh, and Jongbin Ryu, "Layer-wise Curriculum Learning for Efficient LLM Compression", Empirical Methods in Natural Language Processing (EMNLP), 2026
Seungmin Oh, Donggeon Lee, and Jongbin Ryu, "Train Overcomplete, Deploy Compact: Scaling Recovery Capacity for Structured LLM Pruning", Empirical Methods in Natural Language Processing (EMNLP), 2026
Seungmin Oh, Seunghun Kang, and Jongbin Ryu, "Re-calibrated Contrastive Loss for Semantic-Aligned Augmentation in Vision-Language Models", British Machine Vision Conference (BMVC), 2026
Hankyul Kang, Gregor Seifer, Donghyun Lee, and Jongbin Ryu, "Do Your Best and Get Enough Rest for Continual Learning", Computer Vision and Pattern Recognition (CVPR), 2025
Junhyung Ko and Jongbin Ryu, "Channel Propagation Networks for Refreshable Vision Transformer", Winter Conference on Applications of Computer Vision (WACV), 2025
Hankyul Kang and Jongbin Ryu, "Enriching Local Patterns with Multi-Token Attention for Broad-Sight Neural Networks", Winter Conference on Applications of Computer Vision (WACV), 2025
Inhyuk Park, Sungeun Kim, and Jongbin Ryu, "Generative Self-Supervised Learning for Medical Image Recognition", Asian Conference on Computer Vision (ACCV), 2024
Seungmin Oh and Jongbin Ryu, "Neural Substitution for Branch-level Network Re-parameterization", Asian Conference on Computer Vision (ACCV), 2024
Sungeun Kim and Jongbin Ryu, "Unsupervised Hashing Network with Hyper Quantization Tree", British Machine Vision Conference (BMVC), 2024
CVAMD participants including Jongbin Ryu, "Towards long-tailed, multi-label disease classification from chest X-ray: Overview of the CXR-LT challenge", Medical Image Analysis (MedIA), 2024
Inhyuk Park, Wonhwa Kim, and Jongbin Ryu, "Style-KD : Class-Imbalanced Medical Image Classification via Style Knowledge Distillation", Biomedical Signal Processing and Control, 2024
Wongi Park and Jongbin Ryu, "Fine-Grained Self-Supervised Learning with Jigsaw puzzles for medical image classification", Computers in Biology and Medicine, 2024
Hankyul Kang, Namkug Kim, Jongbin Ryu, "Attentional decoder networks for chest X-ray image recognition on high-resolution features", Computer Methods and Programs in Biomedicine, 2024
Seungmin Oh, Namkug Kim, Jongbin Ryu, "Analyzing to discover origins of CNNs and ViT architectures in medical images", Scientific Reports, 2024
Junhyung Ko and Jongbin Ryu, "Spatial Bias for Attention-free Non-local Neural Networks", Expert Systems with Applications, 2024
Seungmin Oh, Jongbin Ryu*, Ho-Jung Shin*, Jeong Ho Song, Sang-Yong, Son, Hoon Hur, Sang-Uk Han (*corresponding author), "Deep learning using computed tomography to identify high-risk patients for acute small bowel obstruction: development and validation of a prediction model", International Journal of Surgery, 2023 (IF 15.3, JCR Top 1%)
Jongbin Ryu*, Dongyoon Han*, Jongwoo Lim (*co-first author), "Gramian Attention Heads are Strong yet Efficient Vision Learners", International Conference on Computer Vision (ICCV), 2023
Wongi Park, Inhyuk Park, Sungeun Kim, and Jongbin Ryu, "Robust Asymmetric Loss for Multi-Label Long-Tailed Learning" (Ranked in the Top-5 at CXR-LT competition), CVAMD workshop at International Conference on Computer Vision (ICCV), 2023
Myeong Seong Yoon, Gitaek Kwon, Jaehoon Oh*, Jongbin Ryu*, Jongwoo Lim, Bo-kyeong Kang, Juncheol Lee, Dong-Kyoon Han (*corresponding author), "Effect of Contrast Level and Image Format on a Deep Learning Algorithm for the Detection of Pneumothorax with Chest Radiography", Journal of Digital Imaging, 2023
Changhee Won, Jongbin Ryu, and Jongwoo Lim, "End-to-End Learning for Omnidirectional Stereo Matching with Uncertainty Prior", IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2021.
Dongjoo Yun, Jongbin Ryu*, Jongwoo Lim (*corresponding author), Dual Aggregated Feature Pyramid Network for Multi Label Classification, Pattern Recognition Letters, 2021
Jongbin Ryu, Ming-Hsuan Yang, and Jongwoo Lim. "Unsupervised feature learning for self-tuning neural networks." Neural Networks, 2021.
Gitaek Kwon*, Jongbin Ryu*, Jaehoon Oh, Jongwoo Lim, Bo-kyeong Kang, Chiwon Ahn, Junwon Bae, and Dong Keon Lee. (*co-first author) "Deep learning algorithms for detecting and visualising intussusception on plain abdominal radiography in children: a retrospective multicenter study." Scientific reports 2020.
Sungeun Hong and Jongbin Ryu (corresponding author), "Attention-Guided Adaptation Factors for Unsupervised Facial Domain Adaptation" Electronics Letters, 2020.
Jongbin Ryu, GiTaek Kwon, Ming-Hsuan Yang, and Jongwoo Lim, "Generalized Convolutional Forest Networks for Domain Generalization and Visual Recognition", International Conference on Learning Representations (ICLR), 2020.
Sungeun Hong and Jongbin Ryu* (corresponding author), "Unsupervised Face Domain Transfer for Low-Resolution Face Recognition", IEEE Signal Processing Letters (SPL), 2020.
Changhee Won, Jongbin Ryu, and Jongwoo Lim, "OmniMVS: End-to-End Learning for Omnidirectional Stereo Matching", IEEE International Conference on Computer Vision (ICCV), 2019.
Changhee Won, Jongbin Ryu, and Jongwoo Lim, "SweepNet: Wide-baseline Omnidirectional Depth Estimation", IEEE International Conference on Robotics and Automation (ICRA), 2019.
Jongbin Ryu, Ming-Hsuan Yang, and Jongwoo Lim, "DFT-based Transformation Invariant Pooling Layer for Visual Classification", European Conference on Computer Vision (ECCV), 2018.
Hakjin Lee, Jongbin Ryu, and Jongwoo Lim, "Joint Object Tracking and Segmentation with Independent Convolutional Neural Networks", Coview: 1st Workshop and Challenge on Comprehensive Video Understanding in the Wild, in conjuction with ACM MM, 2018.
Sungeun Hong, Jongbin Ryu, Woobin Im, and Hyun S. Yang, "D3: Recognizing dynamic scenes with deep dual descriptor based on key frames and key segments", Neurocomputing, 2018.
Sungeun Hong, Jongbin Ryu, and Hyun S. Yang, "Not all frames are equal: aggregating salient features for dynamic texture classification", Multidimensional Systems and Signal Processing, 2018
Sungeun Hong, Woobin Im, Jongbin Ryu and Hyun S. Yang, "SSPP-DAN: Deep Domain Adaptation Network for Face Recognition with Single Sample Per Person", IEEE International Conference on Image Processing (ICIP), 2017.
Jongbin Ryu, and Hyun S. Yang, "Locality-preserving descriptor for robust texture feature representation", Neurocomputing, 2016.
Jongbin Ryu, Sungeun Hong, and Hyun S. Yang, "Sorted consecutive local binary pattern for texture classification", IEEE Transactions on Image Processing (TIP), 2015.
Jongbin Ryu, Hyun S. Yang, and Yongho Seo, "Real time eye blinking detection using local ternary pattern and SVM", International Conference on Broadband and Wireless Computing, Communication and Applications (BWCCA), 2013.
Suwon Lee, Jinki Jung, Jihye Hong, Jongbin Ryu, and Hyun S. Yang , "AR Paint: A Fusion System of a Paint Tool and AR", International Conference on Entertainment Computing (ICEC), 2012.
Jongbin Ryu, Hohyun Park, and Jaehwa Park, "Corner classification using Harris algorithm", Electronics Letters, 2011.
Jongbin Ryu, Changun Lee, and Hohyun Park, "Formula for Harris corner detector", Electronics Letters, 2011.
Jongbin Ryu, and Hohyun Park, "Log-log scaled Harris corner detector", Electronics Letters, 2010.