Jinhong Jung

Assistant Professor, Data Mining Lab., School of Software, Soongsil University

jinhong at ssu.ac.kr

#225, School of Software, Soongsil University

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I am an Assistant Professor in School of Software of Soongsil University, South Korea. Previously, I was an Assistant Professor at Jeonbuk National University and a Postdoctoral Researcher at Seoul National University. I received my Ph.D. from Department of Computer Science and Engineering at Seoul National University, South Korea, in 2020, where I was advised by U Kang and supported by the Global Ph.D. Fellowship. I received my M.S. in Computer Science from KAIST and my B.S. in Computer Science and Engineering from Jeonbuk National University. I won the best student paper runner-up award at ICDM 2023. My research interests include data mining, recommender systems, and graph machine learning, with a particular focus on leveraging large language models.

I lead the Data Mining Lab. in School of Software at Soongsil University.

Position

Assistant Professor
Sep. 2023 - Present

School of Software

Soongsil University

Assistant Professor
Sep. 2020 - Aug. 2023

Department of Computer Science and Engineering

Jeonbuk National University

Postdoctoral Research Fellow
Mar. 2020 - Aug. 2020

Data Mining Lab.

Seoul National University

Awards

PAKDD Best Survey Paper Award @ PAKDD
Jun. 2025
IEEE ICDM Best Student Paper Runner-up Award @ ICDM
Dec. 2023
HumanTech Award (Bronze Prize) @ Samsung
Feb. 2023
AAAI-21 Outstanding Program Committee Award @ AAAI
Feb. 2021
BK21 Plus Excellent Research Award @ SNU
Aug. 2018
· · · More · · ·
HumanTech Award (Honorable Mention) @ Samsung
Jan. 2018
HumanTech Award (Silver Prize) @ Samsung
Feb. 2017
ACM SIGKDD Student Travel Award @ SIGKDD
Jun. 2016
Naver Ph.D. Fellowship @ Naver
Apr. 2016
Global Ph.D. Fellowship @ NRF
Mar. 2016
ACM SIGMOD Student Travel Award @ SIGMOD
Jun. 2015
HumanTech Award (Gold Prize) @ Samsung
Feb. 2015

Awards

PAKDD Best Survey Paper Award

- Awarded by PAKDD
Jun. 2025

IEEE ICDM Best Student Paper Runner-up Award

- Awarded by ICDM
Dec. 2023

HumanTech Award (Bronze Prize)

- Awarded by Samsung
Feb. 2023

AAAI-21 Outstanding Program Committee Award

- Awarded by AAAI
Feb. 2021

BK21 Plus Excellent Research Award

- Awarded by SNU
Aug. 2018
· · · More · · ·

HumanTech Award (Honorable Mention)

- Awarded by Samsung
Jan. 2018

HumanTech Award (Silver Prize)

- Awarded by Samsung
Feb. 2017

ACM SIGKDD Student Travel Award

- Awarded by SIGKDD
Jun. 2016

Naver Ph.D. Fellowship

- Awarded by Naver
Apr. 2016

Global Ph.D. Fellowship

- Awarded by NRF
Mar. 2016

ACM SIGMOD Student Travel Award

- Awarded by SIGMOD
Jun. 2015

HumanTech Award (Gold Prize)

- Awarded by Samsung
Feb. 2015

Publications

  • Refereed Conference and Journal Papers
    1. Do All Nodes Benefit Equally from Knowledge Graphs? Adaptive Node-Aware KG Fusion for Recommendation
      Jaehyun Park, Minseo Jeon, Daewon Gwak, Sunuk Kim, Hanvit Lee, and Jinhong Jung
      CIKM 2026
    2. Personalized Ranking on Cascading Behavior Graphs for Accurate Multi-Behavior Recommendation
      Geonwoo Ko, Minseo Jeon, and Jinhong Jung
      TIST 2026
    3. AlphaFree: Recommendation Free from Users, IDs, and GNNs
      Minseo Jeon, Junwoo Jung, Daewon Gwak, and Jinhong Jung
      WWW 2026
    4. A Comprehensive Survey on Multi-Behavior Recommender Systems: Extended Taxonomy and Recent Advances
      Kyungho Kim, Sunwoo Kim, Geon Lee, Jinhong Jung, and Kijung Shin
      IJDSA 2026
    5. PIGLET: Probabilistic Message Passing for Semi-supervised Link Sign Prediction
      Ka Hyun Park, Junghun Kim, Jinhong Jung, and U Kang
      ICDM 2025
    6. SearchLight: Neural Architecture Search for Lightweight Spatio-Temporal Graph Neural Networks
      Heeyong Yoon, Jinhong Jung, Kang-Wook Chon, and MinSoo Kim
      Access 2025
    7. Effective and Lightweight Representation Learning for Signed Bipartite Graphs
      Gyeongmin Gu, Minseo Jeon, Hyun-Je Song, and Jinhong Jung
      NN 2025
    8. Effective and Lightweight Lossy Compression of Tensors: Techniques and Applications
      Jihoon Ko, Taehyung Kwon, Jinhong Jung, and Kijung Shin
      KAIS 2025
    9. AugWard: Augmentation-Aware Representation Learning for Accurate Graph Classification
      Minjun Kim, Jaehyeon Choi, SeungJoo Lee, Jinhong Jung, and U Kang
      PAKDD 2025
    10. Multi-Behavior Recommender Systems: A Survey
      Kyungho Kim, Sunwoo Kim, Geon Lee, Jinhong Jung, and Kijung Shin
      PAKDD 2025
      · Received the PAKDD 2025 Best Survey Paper Award
    11. ELiCiT: Effective and Lightweight Lossy Compression of Tensors
      Jihoon Ko, Taehyung Kwon, Jinhong Jung, Jun-Gi Jang, and Kijung Shin
      ICDM 2024
      · Selected as one of the best-ranked papers of ICDM 2024 for fast-track journal invitation
    12. Compact Lossy Compression of Tensors via Neural Tensor-Train Decomposition
      Taehyung Kwon, Jihoon Ko, Jun-gi Jang, Jinhong Jung, and Kijung Shin
      KAIS 2024
    13. MuLe: Multi-Grained Graph Learning for Multi-Behavior Recommendation
      Seunghan Lee, Geonwoo Ko, Hyun-Je Song, and Jinhong Jung
      CIKM 2024
    14. Compact Decomposition of Irregular Tensors for Data Compression: From Sparse to Dense to High-Order Tensors
      Taehyung Kwon, Jihoon Ko, Jinhong Jung, Jun-Gi Jang, and Kijung Shin
      KDD 2024
    15. Learning Disentangled Representations in Signed Directed Graphs without Social Assumptions
      Geonwoo Ko and Jinhong Jung
      InfSci 2024
    16. Random Walk with Restart on Hypergraphs: Fast Computation and an Application to Anomaly Detection
      Jaewan Chun, Geon Lee, Kijung Shin, and Jinhong Jung
      DMKD 2023
    17. TensorCodec: Compact Lossy Compression of Tensors without Strong Data Assumptions
      Taehyung Kwon, Jihoon Ko, Jinhong Jung, and Kijung Shin
      ICDM 2023
      · Received the IEEE ICDM Best Student Paper Runner-up Award
      · Selected as one of the best-ranked papers of ICDM 2023 for fast-track journal invitation
    18. NeuKron: Constant-Size Lossy Compression of Sparse Reorderable Matrices and Tensors
      Taehyung Kwon, Jihoon Ko, Jinhong Jung, and Kijung Shin
      WWW 2023
    19. Time-aware Random Walk Diffusion to Improve Dynamic Graph Learning
      Jong-whi Lee and Jinhong Jung
      AAAI 2023
      · Accepted as oral presentation
      · Received the Samsung Humantech Paper Award (Bronze Prize)
    20. Accurate Node Feature Estimation with Structured Variational Graph Autoencoder
      Jaemin Yoo, Hyunsik Jeon, Jinhong Jung, and U Kang
      KDD 2022
    21. Signed Random Walk Diffusion for Effective Representation Learning in Signed Graphs
      Jinhong Jung, Jaemin Yoo, and U Kang
      PLOS ONE 2022
    22. Compressing Deep Graph Convolution Network with Multi-Staged Knowledge Distillation
      Junghun Kim, Jinhong Jung, and U Kang
      PLOS ONE 2021
    23. Learning to Walk across Time for Interpretable Temporal Knowledge Graph Completion
      Jaehun Jung, Jinhong Jung, and U Kang
      KDD 2021
    24. Fast and Accurate Pseudoinverse with Sparse Matrix Reordering and Incremental Approach
      Jinhong Jung and Lee Sael
      ML 2020
    25. Accurate Relational Reasoning in Edge-labeled Graphs by Multi-Labeled Random Walk with Restart
      Jinhong Jung, Woojeong Jin, Ha-Myung Park, and U Kang
      WWWJ 2020
    26. BalanSiNG: Fast and Scalable Generation of Realistic Signed Networks
      Jinhong Jung, Ha-Myung Park, and U Kang
      EDBT 2020
    27. Random Walk Based Ranking in Signed Social Networks: Model and Algorithms
      Jinhong Jung, Woojeong Jin, and U Kang
      KAIS 2019
    28. Supervised and Extended Restart in Random Walks for Ranking and Link Prediction in Networks
      Woojeong Jin, Jinhong Jung, and U Kang
      PLOS ONE 2019
    29. Zoom-SVD: Fast and Memory Efficient Method for Extracting Key Patterns in an Arbitrary Time Range
      Jun-Gi Jang, Dongjin Choi, Jinhong Jung, and U Kang
      CIKM 2018
      · Received the Samsung Humantech Paper Award (Honorable Mention)
    30. TPA: Fast, Scalable, and Accurate Method for Approximate Random Walk with Restart on Billion Scale Graphs
      Minji Yoon, Jinhong Jung, and U Kang
      ICDE 2018
    31. A Comparative Study of Matrix Factorization and Random Walk with Restart in Recommender Systems
      Haekyu Park, Jinhong Jung, and U Kang
      BigData 2017
    32. BePI: Fast and Memory-Efficient Method for Billion-Scale Random Walk with Restart
      Jinhong Jung, Namyong Park, Lee Sael, and U Kang
      SIGMOD 2017
      · Received the Samsung Humantech Paper Award (Silver Prize)
    33. A New Question Answering Approach with Conceptual Graph
      Kyung-Min Kim, Jinhong Jung, Jihee Ryu, Ha-Myung Park, Joseph P.Joohee, Seokwoo Jeong, U Kang, and Sung-Hyon Myaeng
      CORIA 2017
    34. Personalized Ranking in Signed Networks using Signed Random Walk with Restart
      Jinhong Jung, Woojeong Jin, Lee Sael, and U Kang
      ICDM 2016
    35. Random Walk with Restart on Large Graphs Using Block Elimination
      Jinhong Jung, Kijung Shin, Lee Sael, and U Kang
      TODS 2016
    36. BEAR:Block Elimination Approach for Random Walk with Restart on Large Graphs
      Kijung Shin, Jinhong Jung, Lee Sael, and U Kang
      SIGMOD 2015
      · Received the Samsung Humantech Paper Award (Gold Prize)
    37. Revisiting Classic Graph Neural Networks for Hypergraph Node Classification: An Extensive Empirical Study
      Daewon Gwak, Jaehyun Park, Sunuk Kim, and Jinhong Jung
      Access

    Preprints

    1. Learning Disentangled Representations in Signed Directed Graphs without Social Assumptions
      Geonwoo Ko and Jinhong Jung
    2. NeuKron: Constant-Size Lossy Compression of Sparse Reorderable Matrices and Tensors
      Taehyung Kwon, Jihoon Ko, Jinhong Jung, and Kijung Shin
    3. Time-aware Random Walk Diffusion to Improve Dynamic Graph Learning
      Jong-whi Lee and Jinhong Jung
      4. · · · More · · ·
    4. Accurate Node Feature Estimation with Structured Variational Graph Autoencoder
      Jaemin Yoo, Hyunsik Jeon, Jinhong Jung, and U Kang
    5. Signed Graph Diffusion Network
      Jinhong Jung, Jaemin Yoo, and U Kang
    6. T-gap: Learning to Walk across Time for Temporal Knowledge Graph Completion
      Jaehun Jung, Jinhong Jung, and U Kang
    7. TPA: Fast, Scalable, and Accurate Method for Approximate Random Walk with Restart on Billion Scale Graphs
      Minji Yoon, Jinhong Jung, and U Kang
    8. Supervised and Extended Restart in Random Walks for Ranking and Link Prediction in Networks
      Woojeong Jin, Jinhong Jung, and U Kang

    Service

    Program Committee Member

      · CIKM
      2025
      · AAAI
      2021 | 2023 | 2024 | 2025
      · TheWebConf (WWW)
      2022 | 2023 | 2024 | 2025
      · KDD
      2024 | 2025
      · WSDM
      2023 | 2024 | 2025
      · BigComp
      2021 | 2024

    Journal Reviewer

      · NEUNET
      2023
      · ESWA
      2023
      · TKDE
      2022

    External Conference Reviewer

    · NeurIPS 2023 Workshop GLFrontiers
    2023
    · KDD
    2016 | 2017 | 2018 | 2019 | 2020
    · TheWebConf
    2016 | 2017 | 2018 | 2019
    · · · More · · ·
    · ICDM
    2015 | 2018 | 2019
    · WSDM
    2018 | 2019
    · CIKM
    2016 | 2017 | 2018 | 2019 | 2025
    · SAC
    2016 | 2017 | 2018 | 2019 | 2020
    · ECML/PKDD
    2016 | 2017
    · BigComp
    2016 | 2018 | 2020
    · DSAA
    2016
    · BigData
    2016
    · DASFAA
    2023

    Education

    Ph.D. in Computer Science and Engineering
    Feb. 2020

    Seoul National University

    Thesis: Random Walk-based Large Graph Mining Exploiting Real-world Graph Properties

    Advisor: Prof. U Kang

    M.S. in Computer Science
    Aug. 2015

    Korea Advanced Institute of Science and Technology

    Advisor: Prof. U Kang

    B.S. in Computer Science and Engineering
    Feb. 2014

    Jeonbuk National University

    Miscellaneous

    My Students' Awards

    · Minseo Jeon, 2025 AI Seoul Tech Scholarship m.s. @ Seoul Scholarship Foundation
    Nov. 2025
    · Gyeong-Min Gu, Minseo Jeon, KSC 2024 Best Paper Award @ KSC
    Dec. 2024
    · Junwoo Jung, Cheolhee Jeong, KDBC 2024 Best Paper Award (Silver Prize) @ KDBC
    Nov. 2024
    · Daewon Gwak, Jaehyun Park, Jongyoon Choi, Self-Improving AI Competition Award @ ETRI
    Oct. 2024
    · Seunghan Lee, Najeong Chae, Joint AI Competition (Runner-up) @ SWCU Council
    Aug. 2023
    · Jong-whi Lee, HumanTech Award (Bronze Prize) @ Samsung
    Feb. 2023
    · Jong-whi Lee, AAAI-23 Student Scholarship @ AAAI
    Dec. 2022

    Talks or Guest Lectures

    Dec. 2024
    · Random Walk-Based Graph Mining @ Kangwon National University
    Apr. 2024
    Dec. 2023
    Oct. 2023
    · Graph Neural Networks @ Rural Development Administration
    Apr. 2022
    · Machine Learning with Graphs @ Korea Computer Congress
    Jul. 2020
    Jan. 2019
    Jun. 2017
    Jul. 2016

    Patents

    Jul. 2026
    Jan. 2026
    Jan. 2026
    Apr. 2025
    Feb. 2025
    Feb. 2025
    Feb. 2025
    Oct. 2024
    Jul. 2023
    Dec. 2021
    Jul. 2021
    Nov. 2019
    Nov. 2018
    Nov. 2018
    Jan. 2018
    Nov. 2017
    Nov. 2017
    Jan. 2017
    Dec. 2016

    Teaching Experience - Instructor

    · Recommender System @ SSU
    24-1 | 25-1
    · Data Structure @ SSU
    24-1 | 25-1
    · Big Data @ SSU
    23-2 | 24-2
    · Software Analysis and Design @ SSU
    23-2 | 24-2
    · Data Mining @ JBNU
    22-2
    · Algorithm @ JBNU
    21-1 | 22-1 | 23-1
    · Data Structure @ JBNU
    20-2 | 21-2 | 22-2 | 23-1
    · C++ Programming @ JBNU
    21-2

    Miscellaneous

    My Students' Awards

    · Minseo Jeon, 2025 AI Seoul Tech Scholarship m.s.

    - Awarded by Seoul Scholarship Foundation
    Nov, 2025

    · Gyeong-Min Gu, Minseo Jeon, KSC 2024 Best Paper Award

    - Awarded by KSC
    Dec, 2024

    · Junwoo Jung, Cheolhee Jeong, KDBC 2024 Best Paper Award (Silver Prize)

    - Awarded by KDBC
    Nov, 2024

    · Daewon Gwak, Jaehyun Park, Jongyoon Choi, Self-Improving AI Competition Award

    - Awarded by ETRI
    Oct, 2024

    · Seunghan Lee, Najeong Chae, Joint AI Competition (Runner-up)

    - Awarded by SWCU Council
    Aug, 2023

    · Jong-whi Lee, HumanTech Award (Bronze Prize)

    - Awarded by Samsung
    Feb, 2023

    · Jong-whi Lee, AAAI-23 Student Scholarship

    - Awarded by AAAI
    Dec, 2022

    Talks or Guest Lectures

    · Leveraging Real-World Graph Properties for Graph Learning

    - Talked at IPAI Seminar, SNU
    Dec. 2024

    · Random Walk-Based Graph Mining

    - Talked at Kangwon National University
    Apr. 2024

    · Learning Graphs with Random Walks

    - Talked at DMLAB, KAIST
    Dec. 2023

    · Time-aware Random Walk Diffusion to Improve Dynamic Graph Learning

    - Talked at KJDB
    Oct. 2023

    · Graph Neural Networks

    - Talked at Rural Development Administration
    Apr. 2022

    · Machine Learning with Graphs

    - Talked at Korea Computer Congress
    Jul. 2020

    · Personalized Ranking in Signed Networks using Signed Random Walk with Restart

    - Talked at NC Soft
    Jan. 2019

    · BePI: Fast and Memory-efficient Method for Billion-Scale RWR

    - Talked at Korea Computer Congress
    Jun. 2017

    · Fast Random Walk with Restart on Large Graphs using Block Elimination

    - Talked at Naver Labs
    Jul. 2016

    Patents

    Teaching Experience - Instructor

    · Recommender System @ SSU
    24-1 | 25-1
    · Data Structure @ SSU
    24-1 | 25-1
    · Big Data @ SSU
    23-2 | 24-2
    · Software Analysis and Design @ SSU
    23-2 | 24-2
    · Data Mining @ JBNU
    22-2
    · Algorithm @ JBNU
    21-1 | 22-1 | 23-1
    · Data Structure @ JBNU
    20-2 | 21-2 | 22-2 | 23-1
    · C++ Programming @ JBNU
    21-2