Yeon-Chang Lee

Biography: I am an assistant professor in the Artificial Intelligence Graduate School and the Department of Computer Science and Engineering at the Ulsan National Institute of Science and Technology (UNIST). Before joining UNIST, I was a postdoctoral researcher in the School of Computational Science and Engineering at the Georgia Institute of Technology, where I worked with Prof. Srijan Kumar. I received my Ph.D. from Hanyang University under the supervision of Prof. Sang-Wook Kim.

Lab: UNIST Data Intelligence Lab

Contact: yeonchang [at] unist [dot] ac [dot] kr

[ Google Scholar | DBLP ]

Research Interests

Graph Machine Learning: Trustworthy Graph Neural Networks; Graph Representation Learning; Graph-based Downstream Tasks
Recommender Systems: Graph-based Collaborative Filtering; Multi-modal and Domain-specific Recommender Systems
Graph + X: Career Trajectory Prediction; Anomaly Detection; Polarization Modeling

Selected Publications
Please refer to my lab page or Google Scholar for a complete list of my publications.

CAPER: Enhancing Career Trajectory Prediction using Temporal Knowledge Graph and Ternary Relationship [ appendix | code | slides ]
Yeon-Chang Lee, JaeHyun Lee, Michiharu Yamashita, Dongwon Lee, and Sang-Wook Kim
ACM KDD 2025 (acceptance rate: 19% (Aug. Cycle))
CATER: A Cluster-Based Alternative-Term Recommendation Framework for Large-Scale Web Search at NAVER
Jiwon Son, Jaeyoon Kim, Taekin Kim, Yeon-Chang Lee, and Sang-Wook Kim
ACM KDD 2025 (acceptance rate: 22% (Aug. Cycle); applied data science track)
Disentangling, Amplifying, and Debiasing: Learning Disentangled Representations for Fair Graph Neural Networks [ appendix | code | poster ]
Yeon-Chang Lee, Hojung Shin, and Sang-Wook Kim
AAAI 2025 (acceptance rate: 23%)
Towards Fair Graph Anomaly Detection: Problem, Benchmark Datasets, and Evaluation [ code & data | slides ]
{Neng Kai Nigel Neo*, Yeon-Chang Lee*}, Yiqiao Jin, Sang-Wook Kim, and Srijan Kumar
ACM CIKM 2024 (acceptance rate: 23%)
PolarDSN: An Inductive Approach to Learning the Evolution of Network Polarization in Dynamic Signed Networks [ project page | code | slides ]
Min-Jeong Kim, Yeon-Chang Lee, and Sang-Wook Kim
ACM CIKM 2024 (acceptance rate: 23%)
SVD-AE: Simple Autoencoders for Collaborative Filtering [ code ]
Seoyoung Hong, Jeongwhan Choi, Yeon-Chang Lee, Srijan Kumar, and Noseong Park
IJCAI 2024 (acceptance rate: 14%)
Representation Learning in Continuous-Time Dynamic Signed Networks [ code ]
{Kartik Sharma*, Mohit Raghavendra*}, Yeon-Chang Lee, Anand Kumar M, and Srijan Kumar
ACM CIKM 2023 (acceptance rate: 24%)
Predicting Information Pathways Across Online Communities [ code & data | video | slides ]
Yiqiao Jin, Yeon-Chang Lee, Kartik Sharma, Meng Ye, Karan Sikka, Ajay Divakaran, and Srijan Kumar
ACM KDD 2023 (acceptance rate: 22%)
TrustSGCN: Learning Trustworthiness on Edge Signs for Effective Signed Graph Convolutional Networks [ project page | code | poster ]
{Min-Jeong Kim*, Yeon-Chang Lee*}, and Sang-Wook Kim
ACM SIGIR 2023 (acceptance rate: 25%; short papers track)
Disentangling Degree-related Biases and Interest for Out-of-Distribution Generalized Directed Network Embedding [ appendix | code | slides ]
Hyunsik Yoo, Yeon-Chang Lee, Kijung Shin, and Sang-Wook Kim
ACM Web Conference (WWW) 2023 (acceptance rate: 19%; press release: NewsH, UNN, 교수신문)
A Competition-Aware Approach to Accurate TV Show Recommendation [ code ]
Hong-Kyun Bae, Yeon-Chang Lee, Kyungsik Han, and Sang-Wook Kim
IEEE ICDE 2023 (acceptance rate: 31%)
THOR: Self-Supervised Temporal Knowledge Graph Embedding via Three-Tower Graph Convolutional Networks [ project page | code | slides ]
{Yeon-Chang Lee*, JaeHyun Lee*}, Dongwon Lee, and Sang-Wook Kim
IEEE ICDM 2022 (acceptance rate: 20%)
MARIO: Modality-Aware Attention and Modality-Preserving Decoders for Multimedia Recommendation [ project page | slides ]
{Taeri Kim*, Yeon-Chang Lee*}, Kijung Shin, and Sang-Wook Kim
ACM CIKM 2022 (acceptance rate: 23%)
Is It Enough Just Looking at the Title?: Leveraging Body Text To Enrich Title Words Towards Accurate News Recommendation
{Taeho Kim*, Yungi Kim*}, Yeon-Chang Lee, Won-Yong Shin, and Sang-Wook Kim
ACM CIKM 2022 (acceptance rate: 29%; short papers track)
AiRS: A Large-Scale Recommender System at NAVER News [ project page | slides ]
{Hongjun Lim*, Yeon-Chang Lee*}, Jin-Seo Lee, Sanggyu Han, Seunghyeon Kim, Yeongjong Jeong, Changbong Kim, Jaehun Kim, Sunghoon Han, Solbi Choi, Hanjong Ko, Dokyeong Lee, Jaeho Choi, Yungi Kim, Hong-Kyun Bae, Taeho Kim, Jeewon Ahn, Hyun-Soung You, and Sang-Wook Kim
IEEE ICDE 2022 (acceptance rate: 28%; industry and applications track)
Directed Network Embedding with Virtual Negative Edges [ project page | code | slides ]
{Hyunsik Yoo*, Yeon-Chang Lee*}, Kijung Shin, and Sang-Wook Kim
ACM WSDM 2022 (acceptance rate: 20%)
Linear, or Non-Linear, That is the Question! [ code ]
{Taeyong Kong*, Taeri Kim*}, Jinsung Jeon, Jeongwhan Choi, Yeon-Chang Lee, Noseong Park, and Sang-Wook Kim
ACM WSDM 2022 (acceptance rate: 20%)
Adversarial Learning of Balanced Triangles for Accurate Community Detection on Signed Networks
{Yoonsuk Kang*, Woncheol Lee*}, Yeon-Chang Lee, Kyungsik Han, and Sang-Wook Kim
IEEE ICDM 2021 (acceptance rate: 20%)
Look Before You Leap: Confirming Edge Signs in Random Walk with Restart for Personalized Node Ranking in Signed Networks [ project page | code | slides ]
{Wonchang Lee*, Yeon-Chang Lee*}, Dongwon Lee, and Sang-Wook Kim
ACM SIGIR 2021 (acceptance rate: 21%)
Are Negative Links Really Beneficial to Network Embedding? In-Depth Analysis and Interesting Results [ project page | slides ]
Yeon-Chang Lee, Nayoun Seo, and Sang-Wook Kim
ACM CIKM 2020 (acceptance rate: 26%; short papers track)
ASiNE: Adversarial Signed Network Embedding [ project page | code | slides ]
Yeon-Chang Lee, Nayoun Seo, Kyungsik Han, and Sang-Wook Kim
ACM SIGIR 2020 (acceptance rate: 26%)
No, That’s Not My Feedback: TV Show Recommendation Using Watchable Interval [ slides ]
{Kyung-Jae Cho*, Yeon-Chang Lee*}, Kyungsik Han, Jaeho Choi, and Sang-Wook Kim
IEEE ICDE 2019 (acceptance rate: 27%)
gOCCF: Graph-Theoretic One-Class Collaborative Filtering Based on Uninteresting Items [ project page | code | slides ]
Yeon-Chang Lee, Sang-Wook Kim, and Dongwon Lee
AAAI 2018 (acceptance rate: 25%)

Teaching

Undergraduate Courses
- CSE403 Deep Learning (2025F)
- CSE321 Database Systems (2024F)
Graduate Courses
- AI503 AI Toolkits (2024S, 2025S)

Positions

UNIST, Ulsan, South Korea | Dec. 2023 - Present
Assistant Professor, Artificial Intelligence Graduate School
Affiliated Assistant Professor, Department of Computer Science and Engineering
Georgia Institute of Technology, Atlanta, GA, United States | July 2022 - Nov. 2023
Postdoctoral Researcher, School of Computational Science and Engineering (Advisor: Prof. Srijan Kumar)
Hanyang University, Seoul, South Korea | Mar. 2021 - June 2022
Postdoctoral Researcher, Department of Artificial Intelligence (Advisor: Prof. Sang-Wook Kim)

Education

Hanyang University, Seoul, South Korea | Feb. 2021
Ph.D. in Computer Science (Advisor: Prof. Sang-Wook Kim)
Eulji University, Seongnam, South Korea | Feb. 2014
B.S. in Medical Information Technology

Professional Services

Conference Organizer
- ACM CIKM | 2025 (Local Co-Chair)
Conference Area Chair & Senior Program Committee
- ACM KDD | 2025 - 2026
- ACM CIKM | 2025 (Short Papers Track)
Conference Reviewer & Program Committee
- ACM Web Conference (formerly, WWW)
  ㄴ Research Track | 2023 - 2025
  ㄴ Industry Track | 2026
  ㄴ PhD Symposium Track | 2025
- ACM KDD
  ㄴ Research Track | 2023 - 2025
  ㄴ Applied Data Science Track | 2025 - 2026
- AAAI | 2026
- NeurIPS
  ㄴ Datasets and Benchmarks Track | 2023 - 2025
- ACM CIKM | 2025
- ECML PKDD | 2024 - 2025
- IEEE DSAA | 2025
- Learning on Graphs Conference (LoG) | 2022 - 2025
- ACM SAC | 2022 - 2025
- BigComp | 2025
- SDM | 2024
Journal Reviewer: IEEE TKDE (2021, 2024, 2025a, 2025b, 2025c), ACM TORS (2022, 2024a, 2024b, 2025a, 2025b), IEEE TPAMI (2025), Communications of the ACM (2025), ACM TIST (2024), IEEE Transactions on Artificial Intelligence (2023), Neural Networks (2023), Information Sciences (2023), IEEE Transactions on Big Data (2023), ESWA (2023), KAIS (2022), Neurocomputing (2022), IEEE Intelligent Systems (2022), The VLDB Journal (2021), IEEE Access (2019)
External/Emergency Reviewer: ECML PKDD (2023), ACM KDD (2021, 2022), IEEE ICDM (2021, 2022), ACM SIGIR (2021, 2023)

Honors and Awards

Reviewer Recognition & Awards: ACM Web Conference (WWW) Outstanding Reviewer (2024), ACM KDD Excellent Reviewer (2025 Research Track, 2025 ADS Track)
Postdoctoral Fellowship Program (Overseas Track), National Research Foundation of Korea (2022 - 2023)
Best Ph.D. Dissertation Award, Research Institute of Industrial Science, Hanyang University (2021)
AAAI Student Scholarship Award (2018)
NAVER Ph.D. Fellowship Award (2017)
Travel Awards: ACM SAC (2016), ACM CIKM (2020), ACM SIGIR (2020)
Domestic Conference/Workshop Awards
Best Paper / Presentation Awards: KIISE KDBC (2017, 2018), KIPS ASK (2023) / KIISE KCC (2019), NGCML (2020)
Certificate of Appreciation: KIISE KCC (2019, 2024), KIISE KSC (2020, 2021)
Others: KIISE 학부생 논문경진대회 우수상 (2017), HYU BK21Plus 실적 우수대학원생 선정 (2017), 빅데이터 생활형 서비스 연구센터 워크샵 논문 우수상 (2018)

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