Wonbin Kweon

Hello! I am a postdoctoral researcher at the University of Illinois Urbana-Champaign (UIUC).
I received my Ph.D. from POSTECH, advised by Prof. Hwanjo Yu, and subsequently worked as a postdoctoral researcher at POSTECH Institute of Artificial Intelligence.
My research interests include Information Retrieval, Large Language Models, and Trustworthy AI.

Experience

University of Illinois at Urbana-Champaign (UIUC), United States
Postdoctoral Researcher, Siebel School of Computing and Data Science, 2025.04 - Present
Advisor: Prof. Jiawei Han
Pohang University of Science and Technology (POSTECH), South Korea
Postdoctoral Researcher, Institute of Artificial Intelligence, 2024.03 - 2025.03
PIURI Postdoctoral Fellowship
Advisor: Prof. Hwanjo Yu

Education

Pohang University of Science and Technology (POSTECH), South Korea
Ph.D., IT Engineering, 2019.02 - 2024.02
Advisor: Prof. Hwanjo Yu
Pohang University of Science and Technology (POSTECH), South Korea
B.S., Industrial and Management Engineering, 2015.03 - 2019.02
Ranked 1st in the Department
GyeongNam Science High School, South Korea
Early Graduation, 2013.03 - 2015.02

Publications

Controlling Diversity at Inference: Guiding Diffusion Recommender Models with Targeted Category Preferences
*Gwangseok Han, *Wonbin Kweon, Minsoo Kim, Hwanjo Yu (*equal contribution)
KDD, 2025
Uncertainty Quantification and Decomposition for LLM-based Recommendation
Wonbin Kweon, Sanghwan Jang, SeongKu Kang, Hwanjo Yu
WWW, 2025
Improving Scientific Document Retrieval with Concept Coverage-based Query Set Generation
SeongKu Kang, Bowen Jin, Wonbin Kweon, Yu Zhang, Dongha Lee, Jiawei Han, Hwanjo Yu
WSDM, 2025
Continual Collaborative Distillation for Recommender System
*Gyuseok Lee, *SeongKu Kang, Wonbin Kweon, Hwanjo Yu
KDD, 2024
Rectifying Demonstration Shortcut in In-Context Learning
Joonwon Jang, Sanghwan Jang, Wonbin Kweon, Minjin Jeon, Hwanjo Yu
NAACL, 2024
Doubly Calibrated Estimator for Recommendation on Data Missing Not At Random
Wonbin Kweon, Hwanjo Yu
WWW, 2024 Oral presentation (link)
Top-Personalized-K Recommendation
Wonbin Kweon, SeongKu Kang, Sanghwan Jang, Hwanjo Yu
WWW, 2024 (link)
Unbiased, Effective, and Efficient Distillation from Heterogeneous Models for Recommender Systems
SeongKu Kang, Wonbin Kweon, Dongha Lee, Jianxun Lian, Xing Xie, Hwanjo Yu
ACM Transactions on Recommender Systems, 2024
Confidence Calibration for Recommender Systems and Its Applications
Wonbin Kweon
Ph.D. Dissertation, POSTECH (link)
Distillation from Heterogeneous Models for Top-K Recommendation
SeongKu Kang, Wonbin Kweon, Dongha Lee, Jianxun Lian, Xing Xie, Hwanjo Yu
WWW, 2023
Consensus Learning from Heterogeneous Objectives for One-Class Collaborative Filtering
SeongKu Kang, Dongha Lee, Wonbin Kweon, Junyoung Hwang, Hwanjo Yu
WWW, 2022
Obtaining Calibrated Probabilities with Personalized Ranking Models
Wonbin Kweon, SeongKu Kang, Hwanjo Yu
AAAI, 2022 Oral presentation (top-3% among 9,020 papers)
Personalized Distillation for Recommender System
SeongKu Kang, Dongha Lee, Wonbin Kweon, Hwanjo Yu
Knowledge-Based Systems, 2022
Topology Distillation for Recommender System
SeongKu Kang, Junyoung Hwang, Wonbin Kweon, Hwanjo Yu
KDD, 2021
Bidirectional Distillation for Top-K Recommender System
Wonbin Kweon, SeongKu Kang, Hwanjo Yu
WWW, 2021 Oral presentation (link)
Item-side Ranking Regularized Distillation for Recommender System
SeongKu Kang, Junyoung Hwang, Wonbin Kweon, Hwanjo Yu
Information Sciences, 2021
DE-RRD: A Knowledge Distillation Framework for Recommender System
SeongKu Kang, Junyoung Hwang, Wonbin Kweon, Hwanjo Yu
CIKM, 2020
Deep Rating Elicitation for New Users in Collaborative Filtering
Wonbin Kweon, SeongKu Kang, Junyoung Hwang, Hwanjo Yu
WWW, 2020 Oral presentation

Academic Service

[Program Committee / Reviewer]

KDD (ACM SIGKDD Conference on Knowledge Discovery & Data Mining), 2023 - 2025
WWW (ACM The Web Conference), 2024 - 2025
AAAI (Annual AAAI Conference on Artificial Intelligence), 2023 - 2025
ICML (International Conference on Machine Learning), 2024 - 2025
ICLR (International Conference on Learning Representations), 2024 - 2025
ACL (Annual Meeting of the Association for Computational Linguistics), 2025

Honors & Awards

POSTECH PIURI Postdoctoral Fellowship (50,000 USD), 2025
Fourth Prize, The 3rd POSTECH Research Award, 2023
AAAI Student Scholarship, 2022
Third Prize, Kakao Music Playlist Recommendation Competition, 2020
Kwanjeong Educational Foundation Scholarship (15,000 USD), 2017 – 2019
Woori Bank Exchange Student Scholarship for TU Munich in Germany (4,000 USD), 2018
POSTECH Exchange Student Scholarship for TU Munich in Germany (2,000 USD), 2018
POSTECH Admission Scholarship, 2015
Hanseong Sonjaehan Foundation Scholarship (4,000 USD), 2014

Talks & Presentations

Improving Scientific Document Retrieval with Concept Coverage-based Query Set Generation
- WSDM (Hannover), oral presentation, 2025.03
Doubly Calibrated Estimator for Recommendation on Data Missing Not At Random
- WWW (Singapore), oral presentation, 2024.05
Obtaining Calibrated Probabilities with Personalized Ranking Models
- AAAI (Virtual, Vancouver), oral presentation, 2022.02
- UberAI (Virtual, San Francisco), invited by Joseph Wang, 2022.05
- Naver-POSTECH AI Day (Pohang, South Korea), 2022.06
Bidirectional Distillation for Top-K Recommender System
- WWW (Virtual, Ljubljana), oral presentation, 2021.04
Deep Rating Elicitation for New Users in Collaborative Filtering
- WWW (Virtual, Taipei), oral presentation, 2020.04

Patents

Method and Apparatus of Knowledge Distillation from Heterogeneous Models for Reducing Prediction Time of Recommender Systems, South Korea, 2023
Consensus Learning from Heterogeneous Objectives for One-Class Collaborative Filtering, South Korea, 2022

Teaching

Predictive Analytics Modelling (DS30), TA, Hyundai Motors, 2023
Artificial Intelligence (DS20), TA, Hyundai Motors, 2022
Artificial Intelligence, TA, SK Hynix, 2020
Artificial Intelligence, TA, SK Innovation, 2020
Introduction to Data Analysis (CSED226), TA, POSTECH, 2020
Trends on Industrial AI (CSED703H), TA, POSTECH, 2019