Sukwon Yun

Incoming Ph.D. Student, UNC Chapel Hill

swyun@cs.unc.edu

Bio

I am an incoming Ph.D. student in the UNITES Lab at University of North Carolina, Chapel Hill, advised by Prof. Tianlong Chen. Prior to UNC, I obtained an M.S. in ISysE at KAIST, where I was fortunate to be advised by Prof. Chanyoung Park. During my Master's, I was honored with the Best Paper Award at the ICML WCB 2023 and spent wonderful time in Tokyo as a visiting researcher at Tokyo Tech, working with Prof. Tsuyoshi Murata and, Dr. Xin Liu.

My current research intersts ile in AI4Science and Efficient ML. Specifically, I am interested in (A) addressing the inductive bias of Graph Neural Networks (GNNs) and Large Language Models (LLMs) with their (B) application in the field of Computational Biology, particularly single-cell RNA sequencing and Tumor Biology. Additionally, I have recently been focusing on (C) building efficient Sparse Mixture-of-Experts in diverse scientific fields.

News

  • Apr., 2024     A paper got accepted at Briefings in Bioinformatics 2024.
  • Apr., 2024     A paper got accepted at WWW 2024 Workshop on Data-centric Artificial Intelligence (DCAI).
  • Mar., 2024     I will be joining UNITES Lab@UNC Chapel Hill this Fall as a Ph.D. Student!
  • Jan., 2024     A paper got accepted at PAKDD 2024.
  • Oct., 2023     I served as a session chair in the Knowledge Representation 3 session at CIKM 2023.
  • Aug., 2023     Two papers got accepted at CIKM 2023.
  • Jul., 2023     Our paper, “Single-cell RNA-seq data imputation using Feature Propagation” won the Best Paper Award at ICML 2023 Workshop on Computational Biology!
  • Jun., 2023     A paper got accepted for a contributed talk at ICML 2023 Workshop on Computational Biology. Excited to give a talk at Honolulu, Hawai’i!
  • Apr., 2023     A paper got accepted at SIGIR 2023.
  • Aug., 2022     A paper got accepted at CIKM 2022.
  • Jul., 2022     I will be joining Tokyo Tech this Fall-Winter as a visting researcher under supervision of Prof. Tsuyoshi Murata. Looking forward to it!
  • Aug., 2021     I joined DSAIL@KAIST as a Master Student!

    • Publications

    Most recent publications on Google Scholar.
    * indicates equal contribution.

    Single-cell RNA Sequencing Data Imputation Using Bi-level Feature Propagation

    Junseok Lee*, Sukwon Yun*, Yeongmin Kim, Tianlong Chen, Manolis Kellis, Chanyoung Park

    Briefings in Bioinformatics 2024

    Paper

    Noise Robust Graph Learning under Feature-Dependent Graph-Noise

    Yeonjun In, Kanghoon Yoon, Sukwon Yun, Kibum Kim, Sungchul Kim, Chanyoung Park

    WWW 2024 Workshop on Data-centric Artificial Intelligence (DCAI) (Oral)

    Paper

    DEGNN: Dual Experts Graph Neural Network Handling Both Edge and Node Feature Noise

    Tai Hasegawa, Sukwon Yun, Xin Liu, Yin Jun Phua, Tsuyoshi Murata

    PAKDD'24: Pacific-Asia Conference on Knowledge Discovery and Data Mining

    Paper Code

    MUSE: Music Recommender System with Shuffle Play Recommendation Enhancement

    Yunhak Oh*, Sukwon Yun*, Dongmin Hyun, Sein Kim, Chanyoung Park

    CIKM'23: ACM International Conference on Information and Knowledge Management

    Paper Code

    S-Mixup: Structural Mixup for Graph Neural Networks

    Junghurn Kim*, Sukwon Yun*, Chanyoung Park

    CIKM'23 (Short): ACM International Conference on Information and Knowledge Management

    Paper Code

    Single-cell RNA-seq data imputation using Feature Propagation

    Sukwon Yun*, Junseok Lee*, Chanyoung Park

    ICMLW'23: ICML Workshop on Computational Biology (Best Paper Award)

    Paper Slides Code

    MELT: Mutual Enhancement of Long-Tailed User and Item for Sequential Recommendation

    Kibum Kim, Dongmin Hyun, Sukwon Yun, Chanyoung Park

    SIGIR'23: ACM SIGIR Conference on Research and Development in Information Retrieval

    Paper Code

    LTE4G: Long-Tail Experts for Graph Neural Networks

    Sukwon Yun, Kibum Kim, Kanghoon Yoon, Chanyoung Park

    CIKM'22: ACM International Conference on Information and Knowledge Management

    Paper Code

    Single-cell RNA Sequencing Data Imputation Using Bi-level Feature Propagation

    Junseok Lee*, Sukwon Yun*, Yeongmin Kim, Tianlong Chen, Manolis Kellis, Chanyoung Park

    Briefings in Bioinformatics 2024

    Paper

    Noise Robust Graph Learning under Feature-Dependent Graph-Noise

    Yeonjun In, Kanghoon Yoon, Sukwon Yun, Kibum Kim, Sungchul Kim, Chanyoung Park

    WWW 2024 Workshop on Data-centric Artificial Intelligence (DCAI) (Oral)

    Paper

    DEGNN: Dual Experts Graph Neural Network Handling Both Edge and Node Feature Noise

    Tai Hasegawa, Sukwon Yun, Xin Liu, Yin Jun Phua, Tsuyoshi Murata

    PAKDD'24: Pacific-Asia Conference on Knowledge Discovery and Data Mining

    Paper Code

    MUSE: Music Recommender System with Shuffle Play Recommendation Enhancement

    Yunhak Oh*, Sukwon Yun*, Dongmin Hyun, Sein Kim, Chanyoung Park

    CIKM'23: ACM International Conference on Information and Knowledge Management

    Paper Code

    S-Mixup: Structural Mixup for Graph Neural Networks

    Junghurn Kim*, Sukwon Yun*, Chanyoung Park

    CIKM'23 (Short): ACM International Conference on Information and Knowledge Management

    Paper Code

    Single-cell RNA-seq data imputation using Feature Propagation

    Sukwon Yun*, Junseok Lee*, Chanyoung Park

    ICMLW'23: ICML Workshop on Computational Biology (Best Paper Award)

    Paper Slides Code

    MELT: Mutual Enhancement of Long-Tailed User and Item for Sequential Recommendation

    Kibum Kim, Dongmin Hyun, Sukwon Yun, Chanyoung Park

    SIGIR'23: ACM SIGIR Conference on Research and Development in Information Retrieval

    Paper Code

    LTE4G: Long-Tail Experts for Graph Neural Networks

    Sukwon Yun, Kibum Kim, Kanghoon Yoon, Chanyoung Park

    CIKM'22: ACM International Conference on Information and Knowledge Management

    Paper Code

    Vitæ

    Full CV in PDF.

    Sukwon Yun
    swyun@cs.unc.edu