I am an Associate Professor of Computing and AI at Chungnam National University (CNU), where I lead the Data Intelligence Lab (DILAB).

I received my Ph.D. in Data Science from KAIST, where I was advised by Prof. Jae-Gil Lee and Prof. Kyomin Jung. My current research interests include graph machine learning, trustworthy AI, GraphRAG and LLM applications, and recommender systems, with broader interests in the theory and applications of data modeling, mining, and learning.

🔥 News

• 2026.09 · Our paper on traffic forecasting robust to aperiodicity was accepted to NeurIPS 2026.
• 2026.08 · Our paper on few-shot node classification on text-attributed graphs was accepted to CIKM 2026.
• 2026.07 · Our paper on quantile-free uncertainty quantification for GNNs was presented at ICML 2026.
• 2026.07 · Two papers on GraphRAG and recommendation were presented at SIGIR 2026.

🔬 Research Interests

• Graph Machine Learning
• Trustworthy and Reliable AI
• GraphRAG and LLM Applications
• Recommender Systems and Information Retrieval

📝 Recent Publications

NeurIPS

SIMBAD: Spatio-Temporal Traffic Forecasting Robust to Aperiodicity

Daniel Y. Lee, Seungwon Shin, Seunghoon Han, Sungsu Lim*, and Susik Yoon*

NeurIPS 2026 · Regular Paper · Acceptance Rate: 25.7%

ICML

Quantile-Free Uncertainty Quantification in Graph Neural Networks

Soyoung Park, Hwanjun Song, and Sungsu Lim*

ICML 2026 · Regular Paper · Acceptance Rate: 26.6%

SIGIR

StAR: Adaptive Structure-Aware Reranking for Semantic-Structural Alignment in GraphRAG

Junghyun Oh and Sungsu Lim*

SIGIR 2026 · Short Paper · Acceptance Rate: 26.7%

SIGIR

DisCoRec: Disentangled Conformity-aware Recommendation with LLM-Guided Multi-View Learning

Minkyung Song, Soyoung Park*, and Sungsu Lim*

SIGIR 2026 · Short Paper · Acceptance Rate: 26.7%

WACV

MR-Pruner: Training-free Multi-resolution Visual Token Pruning for Multi-modal Large Language Models

Seunghoon Han, Hyewon Lee, Soyoung Park, Jong-Ryul Lee*, and Sungsu Lim*

WACV 2026 · Regular Paper · Acceptance Rate: 33.7%

🎖 Honors and Awards

• 2026: CNU Teaching Award Candidate (Top 7% among faculty; selection in progress)
• 2025: CNU President’s Commendation for Outstanding Faculty Member
• 2023–2026: Outstanding Young Researchers Grant, NRF of Korea
• 2023: KSEE Young Engineering Educator Award
• 2022: NVIDIA Applied Research Accelerator Award
• 2022: CNU Teaching Award (Top 1% among faculty)
• 2021: Commissioner’s Citation, Korea Customs Service
• 2021: Best Paper Award (3rd Place), IEEE BigComp
• 2016: Qualcomm Innovation Award
• 2014: KT ICT Award, Big Data Analysis Contest (Big Contest)
• 2012: Nomination Award, Microsoft Research Asia Fellowship
• 2012: Honorable Mention, Samsung Humantech Paper Award

💼 Experience

• 2023–present: Associate Professor, Chungnam National University
• 2024–2025: Advisor & Visiting Researcher, Nota AI, Sunnyvale, CA, USA
• 2020-2024: Advisor, Institute of Science Education for the Gifted, Chungnam National University
• 2018–2023: Assistant Professor, Chungnam National University
• 2013–2016: Research Assistant, Data Mining Lab., KAIST (Advisor: Jae-Gil Lee)
• 2010–2013: Research Assistant, Applied Algorithm Lab., KAIST (Advisor: Kyomin Jung)
• 2009-2011: Research Assistant, Statistical Lab., KAIST (Advisor: Sung-Ho Kim)

📖 Education

• 2016: Ph.D. in Data Science, KAIST
• 2011: M.S. in Mathematical Sciences, KAIST
• 2009: B.S. in Mathematical Sciences, KAIST
• 2004: Chungnam Science High School (early graduation)

👥 Data Intelligence Lab

I have led the Data Intelligence Lab (DILAB) since 2018. Our research focuses on graph machine learning, trustworthy AI, GraphRAG and LLMs, and recommender systems.

📢 We are recruiting graduate students. Please contact me at sungsu@cnu.ac.kr if interested.

🎓 Teaching @ CNU

• Graduate: Machine Learning with Graphs, Lightweight Deep Learning, Topics in Data Mining, Advanced Algorithms, etc.

• Undergraduate: Deep Learning, Data Science, Math for AI, Numerical Analysis, Linear Algebra, Discrete Math, etc.

🤝 Professional Service

• Organizing Committee: KDD 2026 (Poster Chair), BigComp 2027 (Social Media Chair), KCC 2026, KCC 2022, etc.
• Program Committee: AAAI, SIGIR, CIKM, DASFAA, PAKDD, ECAI, BigData, BigComp, KSIAM Spring/Fall, etc.
• Editorial Board Member: Frontiers in Big Data, Journal of KIISE, Communications of KIISE, etc.
• Reviewer: Proceedings of the IEEE, IEEE TKDE, VLDB Journal, Information Sciences, ML Conferences, etc.
• Advisory Board Member: Daejeon AI Innovation Strategy, Ministry of Data and Statistics, KISTI DataON, etc.

🎤 Invited Talks

• 2026: Graph Learning: Representation, Recommendation, Reasoning, and Reliability, UNIST CSE
• 2026: The Current State of AI, Daejeon Metropolitan Council
• 2026: Generative & Trustworthy AI, Chungnam National University Hospital
• 2026: Trustworthy AI, Korea Astronomy and Space Science Institute