Hello! I earned a Ph.D. in Computer Science from Korea University, where I was a member of the Data Mining and Information Systems (DMIS) Lab advised by Prof. Jaewoo Kang (and co-advised by Prof. Hyunwoo J. Kim for one year). During my PhD course, I completed the Intensive Artificial Intelligence Program at Carnegie Mellon University and spent time as a visiting student under the supervision of Prof. Leman Akoglu. I worked as an AI research intern at LG AI Research for nine months (hosted by Soonyoung Lee, Ph.D.), and at KakaoBrain for six months (hosted by Eun-Sol Kim, Ph.D.). Prior to my PhD studies, I earned a Bachelor's degree in Biomedical Engineering from Korea University.
My research area encompasses the broad field of machine learning, with a focus on representation learning for graph-structured data. I am also interested in applying machine learning techniques to diverse domains, including computer vision and bioinformatics.
[ dʒun.hjʌn liː ]
[Under Review] Cold-Start Recommendation with Knowledge-Guided Retrieval-Augmented Generation
Wooseong Yang, Weizhi Zhang, Yuqing Liu, Yuwei Han, Yu Wang, Junhyun Lee†, Philip S. Yu†
[Under Review] From Static Benchmarks to Dynamic Protocol: Agent-Centric Text Anomaly Detection for Evaluating LLM Reasoning
Seungdong Yoa, Sanghyu Yoon, Suhee Yoon, Dongmin Kim, Ye Seul Sim, Junhyun Lee†, Woohyung Lim†
[Under Review] Beyond Association: A Causal Perspective on Multi-Resolution Aggregation in Multiple-Instance Learning for Whole Slide Image Analysis
Junhyun Lee, Soonyoung Lee, Jongseong Jang†
[Under Review] Mitigating Multi-Resolution Dilemma of Whole Slide Images via Spectral Approaches
Junhyun Lee, Jongseong Jang, Soonyoung Lee, Bumsoo Kim†
[Under Review] Subgraph-level Universal Prompt Tuning
Junhyun Lee, Wooseong Yang, Jaewoo Kang†
[KDD 2025] Understanding and Tackling Over-Dilution in Graph Neural Networks
Junhyun Lee, Veronika Thost, Bumsoo Kim, Jaewoo Kang†, Tengfei Ma†
Seungheun Baek*, Soyon Park*, Yan Ting Chok, Junhyun Lee, Jueon Park, Mogan Gim†, Jaewoo Kang†
[NeurIPS 2024] TurboHopp: Accelerated Molecule Scaffold Hopping with Consistency Models
Kiwoong Yoo, Owen Oertell, Junhyun Lee, Sanghoon Lee, Jaewoo Kang†
[Bioinformatics / ISMB 2024] MolPLA: A Molecular Pretraining Framework for Learning Cores, R-Groups and their Linker Joints
Mogan Gim*, Jueon Park*, Soyon Park, Sanghoon Lee, Seungheun Baek, Junhyun Lee, Ngoc-Quang Nguyen, Jaewoo Kang†
[IEEE Access 2023] Co-attention Graph Pooling for Efficient Pairwise Graph Interaction Learning
Junhyun Lee*, Bumsoo Kim*, Minji Jeon†, Jaewoo Kang†
[ECAI 2023] Towards Flexible Time-to-event Modeling: Optimizing Neural Networks via Rank Regression
Hyunjun Lee*, Junhyun Lee*, Taehwa Choi, Jaewoo Kang†, Sangbum Choi†
[CVPR 2022] MSTR: Multi-Scale Transformer for End-to-End Human-Object Interaction Detection
Bumsoo Kim, Jonghwan Mun, Kyoung-Woon On, Minchul Shin, Junhyun Lee, Eun-Sol Kim†
[NeurIPS 2021] Neo-GNNs: Neighborhood Overlap-aware Graph Neural Networks for Link Prediction
Seongjun Yun, Seoyoon Kim, Junhyun Lee, Jaewoo Kang†, Hyunwoo J. Kim†
[CVPR 2021 (Oral)] HOTR: End-to-End Human-Object Interaction Detection with Transformers (Cited by over 300)
Bumsoo Kim, Junhyun Lee, Jaewoo Kang, Hyunwoo J Kim†, Eun-sol Kim†
[ACS Appl. Mater. Interfaces 2020] 3D Printed, Customizable, and Multifunctional Smart Electronic Eyeglasses for Wearable Healthcare Systems and Human–Machine Interfaces
Joong Hoon Lee, Hanseop Kim, Ji-Young Hwang, Jinmook Chung, Tae-Min Jang, Dong Gyu Seo, Yuyan Gao, Junhyun Lee, Haedong Park, Seungwoo Lee, Hong Chul Moon, Huanyu Cheng, Sang-Hoon Lee, Suk-Won Hwang†
[ECCV 2020 Workshop] Robust Long-Term Object Tracking via Improved Discriminative Model Prediction
Seokeon Choi, Junhyun Lee, Yunsung Lee, Alexander Hauptmann†
[ICML 2019] Self-Attention Graph Pooling (Cited by over 1,500)
Junhyun Lee*, Inyeop Lee*, Jaewoo Kang†
Data Mining & Information Systems Lab (advisor: Prof. Jaewoo Kang)
                            - AI Program at Language Technologies Institute
                            - Data Analysis Techniques Algorithms Lab (advisor: Prof. Leman Akoglu)
                        
Intelligent Bio-MEMS Lab (advisor: Prof. Sang-Hoon Lee)
                            AI Research Intern Multimodal lab (leader: Soonyoung Lee, Ph.D.)
                            - Medical squad (leader: Jongseong Jang, Ph.D.)
                            - Performed research on medical data analysis
                        
                            Instructor High-level computer vision course
                            - Designed and implemented curriculum for graph and transformer-based approaches
                        
                            AI Research Intern Video intelligence team (host: Eun-Sol Kim, Ph.D.)
                            - Performed research on high-level computer vision for video understanding
                        
Researcher Big data scientist training team (host: Prof. Jaewoo Kang)
                            Research Intern Biomedical electrode team (host: Prof. Sang-Hoon Lee)
                            - Developed human-machine interface applications using biomedical signals
                            - Fabricated elastic electrodes using carbon nanotubes and polydimethylsiloxane
                        
                            - Developed a novel deep learning model to generate molecular graph representations and integrate gene expression data
                            - Constructed drug-kinase binding affinity prediction model
                            - Developed a novel graph pooling module to predict drug-drug interactions
                        
                            - Developed the webserver (Back-end) using Django, Nginx, and Gunicorn
                            - Developed Front-end using HTML, CSS and JavaScript
                            - Served on both RaspberryPi (for hardware interactions) and AWS
                            - URL: https://zozo.works
                            - URL: https://fromzero.studio 
                        
                            - Developed object detection model for white blood cell microscopic image
                            - Implemented medical image segmentation model
                            - Developed labeling tool (PyQt 5) for medical image segmentation
                        
                            - Performed a preliminary study for clinical decision support systems on deep learning
                            - Developed the webserver for deep learning model inference APIs (Flask)
                        
                            - Fabricated composite of carbon nanotube and polydimethylsiloxane
                            - Performed toxicity test of the electrode with HaCaT cell line
                            - Developed a Human-Machine Interface Application using EOG (Electrooculography)
                        
                            - Developed the end-to-end wireless authentication system using ECG(ElectroCardioGram)
                            - Fabricated elastic electrodes using carbon nanotubes and polydimethylsiloxane
                            - Designed analog signal processing circuit and DAQ 
                            - Developed Bluetooth communication, digital signal processing, and GUI
                        
                            - Developed programs for generation of personal barcodes and a barcode reader
                            - Developed a kiosk program for college reading room seat allocation [link to photos]
                        
A Korean community for Graph Neural Networks
                            - [Organizer] Learning on Graphs Conference (2024 - present)
                            - [Reviewer] Learning on Graphs Conference (2022 - present)
                            - [Program Committee] Graph Learning Workshop at The Web Conference (2022) [link to web archive]
                        
                            - International Conference on Learning Representations (ICLR, 2022 - present)
                            - International Conference on Machine Learning (ICML, 2021 - present)
                            - Conference on Neural Information Processing Systems (NeurIPS, 2021 - present)
                            - International Joint Conference on Artificial Intelligence (IJCAI, 2025 - present)
                            - AAAI Conference on Artificial Intelligence (AAAI, 2026 - present)
                        
                            - IEEE Conference on Computer Vision and Pattern Recognition (CVPR, 2023 - present)
                            - IEEE International Conference on Computer Vision (ICCV, 2023 - present)
                            - European Conference on Computer Vision (ECCV, 2024 - present)
                            - Asian Conference on Computer Vision (ACCV, 2024 - present)
                        
                            - ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD, 2024 - present)
                               Recognized as an Outstanding Reviewer at KDD 2025
                               Served as a Session Chair at KDD 2025
                        
                            - IEEE Transactions on Circuits and Systems for Video Technology (TCSVT)
                            - Information Sciences
                            - Computer Vision and Image Understanding (CVIU)
                            - Engineering Applications of Artificial Intelligence (EAAI)
                            - Neurocomputing
                            - Artificial Intelligence In Medicine
                            - Applied Soft Computing
                            - Knowledge-Based Systems
                        
Cleveland Clinic @Ohio, USA
Korea Computer Congress @Jeju, South Korea
Kakao Corp. @Pangyo, South Korea
IDG-DREAM Drug-Kinase binding prediction challenge (Team: DMIS_DK)
Scholarship due to a volunteer kiosk project [link to Univ News Article (Korean)]