Research Interests

• Graph Machine Learning: Graph Representation Learning; Dynamics, Robustness, and Fairness in Graph Mining; Graph-based Downstream Tasks

• Recommender Systems: Graph-based Collaborative Filtering; Multi-modal and Domain-specific Recommender Systems

• Graph + X: Career Trajectory Prediction; Anomaly Detection; Counter Misinformation

Selected Publications 

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

• SVD-AE: Simple Autoencoders for Collaborative Filtering
  Seoyoung Hong, Jeongwhan Choi, Yeon-Chang Lee, Srijan Kumar, and Noseong Park
  IJCAI 2024 (acceptance rate: TBA)

• A Survey of Graph Neural Networks for Social Recommender Systems [ project page ]
  {Kartik Sharma*, Yeon-Chang Lee*}, Sivagami Nambi, Aditya Salian, Shlok Shah, Sang-Wook Kim, and Srijan Kumar
  ACM Computing Surveys 2024 (SCIE journal, impact factor: 16.6)

• 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: 24.04%)

• 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: 22.10%)

• 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: 25.12%; 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: 19.21%; 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: 30.61%)

• A Framework for Accurate Community Detection on Signed Networks Using Adversarial Learning
  Yoonsuk Kang, Woncheol Lee, Yeon-Chang Lee, Kyungsik Han, and Sang-Wook Kim
  IEEE TKDE 2023 (SCIE journal, impact factor: 9.23)

• 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: 19.66%)

• 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: 23.32%)

• 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: 28.57%; 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: 20.23%)

• 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: 20.23%)

• 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: 20.00%)

• 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: 20.97%)

• 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: 25.94%; 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: 26.48%)

• 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: 26.80%)

• 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: 24.55%)

Teaching

• CSE321 Database Systems  |  Fall 2024

• AI503 AI Toolkits (code shared with CSE613)  |  Spring 2024

Positions

• UNIST, Ulsan, South Korea  |  Dec. 2023 - Present
  Assistant Professor, Artificial Intelligence Graduate School
  Adjunct 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

• Program Committee Member and Conference Reviewer
  ACM Web Conference (formerly, WWW)  |  2023 - 2024
  ACM KDD  |  2023 - 2024
  ECML PKDD  |  2024
  SDM  |  2024
  NeurIPS Datasets and Benchmarks Track  |  2023 - 2024
  Learning on Graphs Conference (LoG)  |  2022 - 2023
  ACM SAC  |  2022 - 2024

• External/Emergency Reviewer: ECML PKDD (2023), ACM KDD (2021, 2022), IEEE ICDM ( 2021, 2022), ACM SIGIR (2021, 2023)

• Journal Reviewer: IEEE TKDE (2021, 2024), ACM TIST (2024), ACM TORS (2022, 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)

Honors and Awards

• Outstanding Reviewer Award, ACM Web Conference (WWW) (2024) [ link ]

• 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), KIISE KSC (2020, 2021)
  Others: KIISE 학부생 논문경진대회 우수상 (2017), HYU BK21Plus 실적 우수대학원생 선정 (2017), 빅데이터 생활형 서비스 연구센터 워크샵 논문 우수상 (2018)