Hyunsik Yoo
Ph.D. student in Computer Science at IL, UIUC
Contact: hy40_[at]_illinois.edu
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Biography
I am a Ph.D. student in Computer Science at the University of Illinois Urbana-Champaign, fortunate to be advised by Prof. Hanghang Tong and to be part of iDEA-iSAIL joint lab. I earned both my M.S. and B.S. in Computer Science from Hanyang University, where I was fortunate to be advised by Prof. Sang-Wook Kim.
My research generally lies in data mining and machine learning. My current focus is on personalized intelligence systems—such as recommender systems, personalized LLMs, and agentic memory—that are temporally adaptable, trustworthy, and user-inclusive.
Interests
Machine Learning, Recommender Systems, Personalized LLMs, Algorithmic Fairness and Robustness, Continual Learning, User-inclusive Systems
Tutorial
Continual Recommender Systems: A Focus on LLMs and Evolving Trends
Seunghan Lee, Seunghyun Baek, Dojun Hwang, Hyunsik Yoo, and SeongKu Kang
DASFAA Tutorial 2026 [webpage]
Continual Recommender Systems
Hyunsik Yoo, SeongKu Kang, Hanghang Tong
CIKM 2025 Tutorial [paper | webpage | slides: Part 1/2/3/4/5 ]
Publication
SCOUT: Coupling-Free Bounds for Trillion-Scale Top-k Retrieval in Sparse Tensor Factorization
Jun-Gi Jang, Hyunsik Yoo, Ruizhong Qiu, Yinglong Xia, and Hanghang Tong
SIGMOD 2027
Reinforcement Routing for Mixtures of LoRAs in Parameter-Efficient LLM Finetuning
Ruizhong Qiu, Hanqing Zeng, Yinglong Xia, Yiwen Meng, Ren Chen, Jiarui Feng, Dongqi Fu, Qifan Wang, Jiayi Liu, Jun Xiao, Xiangjun Fan, Benyu Zhang, Hong Li, Zhining Liu, Hyunsik Yoo, Zhichen Zeng, Tianxin Wei, and Hanghang Tong
COLM 2026
Continual Low-Rank Adapters for LLM-based Generative Recommender Systems
Hyunsik Yoo, Ting-Wei Li, SeongKu Kang, Zhining Liu, Charlie Xu, Qilin Qi, and Hanghang Tong
ICLR 2026 [paper | code]
Mixture of Sequence: Theme-Aware Mixture-of-Experts for Long-Sequence Recommendation
Xiao Lin, Zhicheng Tang, Weilin Cong, Mengyue Hang, Kai Wang, Yajuan Wang, Zhichen Zeng, Ting-Wei Li, Hyunsik Yoo, Zhining Liu, Xuying Ning, Ruizhong Qiu, Wen-Yen Chen, Shuo Chang, Rong Jin, Huayu Li and Hanghang Tong
WWW 2026
Capturing User Interests from Data Streams for Continual Sequential Recommendation
Gyuseok Lee, Hyunsik Yoo, Junyoung Hwang, SeongKu Kang, and Hwanjo Yu
WSDM 2026
Embracing Plasticity: Balancing Stability and Plasticity in Continual Recommender System
Hyunsik Yoo, SeongKu Kang, Ruizhong Qiu, Charlie Xu, Fei Wang, and Hanghang Tong
Generalizable Recommender System During Temporal Popularity Distribution Shifts
Hyunsik Yoo, Ruizhong Qiu, Charlie Xu, Fei Wang, Hanghang Tong
Class-Imbalanced Graph Learning without Class Rebalancing
Zhining Liu, Ruizhong Qiu, Zhichen Zeng, Hyunsik Yoo, David Zhou, Zhe Xu, Yada Zhu, Kommy Weldemariam, Jingrui He, Hanghang Tong [paper | code]
ICML 2024
Ensuring User-side Fairness in Dynamic Recommender Systems
Hyunsik Yoo, Zhichen Zeng, Jian Kang, Ruizhong Qiu, David Zhou, Zhining Liu, Fei Wang, Charlie Xu, Eunice Chan, and Hanghang Tong [paper | code | arxiv (latest update) ]
WWW 2024 | Oral presentation (link)
Disentangling Degree-related Biases and Interest for Out-of-Distribution Generalized Directed Network Embedding [paper | code]
Hyunsik Yoo, Yeon-Chang Lee, Kijung Shin, and Sang-Wook Kim
WWW 2023
Directed Network Embedding with Virtual Negative Edges [paper | project page | code]
Hyunsik Yoo*, Yeon-Chang Lee*, Kijung Shin, and Sang-Wook Kim
WSDM 2022
Education
Education
University of Illinois Urbana-Champaign, Illinois, U.S.
Ph.D. in Computer Science, Aug. 2022 - Present
Advisor: Prof. Hanghang Tong
Hanyang University, Seoul, South Korea
M.S. in Computer Science, Mar. 2020 - Feb. 2022
Advisor: Prof. Sang-Wook Kim
B.S. in Computer Science & Engineering, Mar. 2013 - Feb. 2020
(Period includes 21 months of military service in Republic of Korea Army)
Positions
Airbnb, San Fransico, CA, US (remote)
Machine Learning Engineering Intern, Jun. 2026 - Aug. 2026
Mentors: Dr. Huiji Gao & Dr. Wendy Wei
Amazon, Seattle, WA, US
Applied Scientist Intern, May. 2025 - Aug. 2025
Mentors: Dr. Qilin Qi & Dr. Charlie Xu
Amazon, Seattle, WA, US
Applied Scientist Intern, May. 2024 - Aug. 2024
Mentors: Dr. Zhen Wen & Dr. Charlie Xu
ECIT, Queen's University Belfast, Northern Ireland, UK
Research Intern, Sept. 2018 - Dec. 2018
Mentors: Dr. BooJoong Kang
Honors & Awards
KDD 2025 Excellent Reviewer, 2025
KDD 2025 NSF Student Travel Award, 2025
SIGIR 2025 NSF Student Travel Award, 2025
Summa Cum Laude Graduation Honors, 2020
Academic Excellence Award (Top 3% in CS), 2017, 2018
Excellent Mentoring Team Award, 2017
Teaching
Teaching Assitant
UIUC. CS412 Introduction to Data Mining, Fall 2025
UIUC. CS412 Introduction to Data Mining, Fall 2023
Tutor
Hanyang Univ. Python training for high school students (student volunteer), Spring 2019
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