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 at Soongsil University. I received my Ph.D. in Computer Science and Engineering from Seoul National University, where I was advised by Prof. U Kang and supported by the Global Ph.D. Fellowship. I received M.S. in Computer Science from KAIST, and B.S. in Computer Science and Engineering from Jeonbuk National University. I was a postdoctoral researcher at Data Mining Lab in Seoul National University. I was an assistant professor at Jeonbuk National University. My research interests include graph machine learning, large-scale data analytics, and applied data science.

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

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

IEEE ICDM Best Student Paper Runner-up Award @ ICDM
Dec. 2023
Humantech Paper Award (Bronze Prize, Advisor) @ Samsung
Feb. 2023
AAAI-21 Outstanding Program Committee Award @ AAAI
Feb. 2021
BK21 Plus Excellent Research Award @ SNU
Aug. 2018
Humantech Paper Award (Honorable Mention, Co-author) @ Samsung
Feb. 2018
· · · More · · ·
Humantech Paper Award (Silver Prize) @ Samsung
Feb. 2017
Global Ph.D. Fellowship Program @ NRF
Mar. 2016 — Feb. 2019
ACM SIGKDD Student Travel Award @ ACM
Jun. 2016
Naver Ph.D. Fellowship Award @ NAVER
Apr. 2016
ACM SIGMOD Student Travel Award @ ACM
Jun. 2015
Humantech Paper Award (Gold Prize, Co-author) @ Samsung
Feb. 2015
National Scholarship @ KAIST
2014 - 2015
National Science & Technology Scholarship @ KSF
2012 - 2013

Awards

IEEE ICDM Best Student Paper Runner-up Award

- Awarded by ICDM
Dec. 2023

Humantech Paper Award (Bronze Prize, Advisor)

- 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

Humantech Paper Award (Honorable Mention, Co-author)

- Awarded by Samsung
Feb. 2018
· · · More · · ·

Humantech Paper Award (Silver Prize)

- Awarded by Samsung
Feb. 2017

Global Ph.D. Fellowship Program

- Awarded by NRF
Mar. 2016 — Feb. 2019

ACM SIGKDD Student Travel Award

- Awarded by ACM
Jun. 2016

Naver Ph.D. Fellowship Award

- Awarded by NAVER
Apr. 2016

ACM SIGMOD Student Travel Award

- Awarded by ACM
Jun. 2015

Humantech Paper Award (Gold Prize, Co-author)

- Awarded by Samsung
Feb. 2015

National Scholarship

- Awarded by KAIST
2014 - 2015

National Science & Technology Scholarship

- Awarded by KSF
2012 - 2013

Publications

  • Refereed Conference and Journal Papers
    1. Compact Lossy Compression of Tensors via Neural Tensor-Train Decomposition
      Jihoon Ko, Taehyung Kwon, Jinhong Jung, Jun-Gi Jang, and Kijung Shin
      Knowledge and Information Systems
    2. ELiCiT: Effective and Lightweight Lossy Compression of Tensors
      Jihoon Ko, Taehyung Kwon, Jinhong Jung, and Kijung Shin
      ICDM 2024
    3. MuLe: Multi-Grained Graph Learning for Multi-Behavior Recommendation
      Seunghan Lee✶, Geonwoo Ko✶, Hyun-Je Song, and Jinhong Jung
      CIKM 2024
    4. 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
    5. Learning Disentangled Representations in Signed Directed Graphs without Social Assumptions
      Geonwoo Ko and Jinhong Jung
      Information Sciences
    6. Random Walk with Restart on Hypergraphs: Fast Computation and an Application to Anomaly Detection
      Jaewan Chun, Geon Lee, Kijung Shin, and Jinhong Jung
      Data Mining and Knowledge Discovery
    7. 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
    8. NeuKron: Constant-Size Lossy Compression of Sparse Reorderable Matrices and Tensors
      Taehyung Kwon, Jihoon Ko, Jinhong Jung, and Kijung Shin
      TheWebConf 2023
    9. 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)
    10. Accurate Node Feature Estimation with Structured Variational Graph Autoencoder
      Jaemin Yoo, Hyunsik Jeon, Jinhong Jung, and U Kang
      KDD 2022
    11. Signed Random Walk Diffusion for Effective Representation Learning in Signed Graphs
      Jinhong Jung, Jaemin Yoo, and U Kang
      PLoS ONE
    12. Learning to Walk across Time for Interpretable Temporal Knowledge Graph Completion
      Jaehun Jung, Jinhong Jung, and U Kang
      KDD 2021
    13. Compressing Deep Graph Convolution Network With Multi-staged Knowledge Distillation
      Junghun Kim, Jinhong Jung, and U Kang
      PLoS ONE
    14. Fast and Accurate Pseudoinverse with Sparse Matrix Reordering and Incremental Approach
      Jinhong Jung and Lee Sael
      Machine Learning
    15. Accurate Relational Reasoning in Edge-labeled Graphs by Multi-Labeled Random Walk with Restart
      Jinhong Jung, Woojeong Jin, Ha-Myung Park, and U Kang
      World Wide Web Journal
    16. BalanSiNG: Fast and Scalable Generation of Realistic Signed Networks
      Jinhong Jung, Ha-Myung Park, and U Kang
      EDBT 2020
    17. Random Walk Based Ranking in Signed Social Networks: Model and Algorithms
      Jinhong Jung, Woojeong Jin, and U Kang
      Knowledge and Information Systems
    18. Supervised and Extended Restart in Random Walks for Ranking and Link Prediction in Networks
      Woojeong Jin, Jinhong Jung, and U Kang
      PLoS ONE
    19. Zoom-SVD: Fast and Memory Efficient Method for Extracting Key Pattern an Arbitrary Time Range
      Jun-gi Jang, Dongjin Choi, Jinhong Jung, and U Kang
      CIKM 2018
    20. 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
    21. A Comparative Study of Matrix Factorization and Random Walk with Restart in Recommender Systems
      Haekyu Park, Jinhong Jung, and U Kang
      BigData 2017
    22. A New Question Answering Approach with Conceptual Graphs
      Kyung-Min Kim, Jinhong Jung, Jihee Ryu, Ha-Myung Park, Joseph P.Joohee, Seokwoo Jeong, U Kang, and Sung-Hyon Myaeng
      CORIA 2017
    23. BePI: Fast and Memory-Efficient Method for Billion-Scale Random Walk with Restart
      Jinhong Jung, Namyong Park, Lee Sael, and U Kang
      SIGMOD 2017
    24. Personalized Ranking in Signed Networks using Signed Random Walk with Restart
      Jinhong Jung, Woojeong Jin, Lee Sael, and U Kang
      ICDM 2016
    25. Random Walk with Restart on Large Graphs Using Block Elimination
      Jinhong Jung, Kijung Shin, Lee Sael, and U Kang
      Transactions on Database Systems
    26. BEAR: Block Elimination Approach for Random Walk with Restart on Large Graphs
      Kijung Shin, Jinhong Jung, Lee Sael, and U Kang
      SIGMOD 2015

    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

      · 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

    Miscellaneous

    My Students' Awards

    · Seunghan Lee & Najeong Chae, Joint AI Competition (Runner-up) @ SWCU Council
    Aug. 2023
    · Jong-whi Lee, Humantech Paper Award (Bronze Prize) @ Samsung
    Feb. 2023
    · Jong-whi Lee, AAAI-23 Student Scholarship @ AAAI
    Dec. 2022

    Projects

    · Representation Learning for Mining Signed Graphs @ NRF
    2021-Present
    · Artificial intelligence innovation hub R&D @ IITP
    2021-Present
    · Model Compression for Deep Graph Neural Networks (SW-StarLab) @ IITP
    2020
    · Fast Ranking in Large-scale Graphs via Link Analysis @ NRF
    2017-2019
    · Knowledge Based News Map Generation @ NC Soft
    2018-2019
    · Deep Learning Techniques on Graphs for QA systems (Exobrain) @ IITP
    2017-2019
    · Event Retrieval and Mining from Unstructured Texts @ NC Soft
    2017-2018
    · Partial Subgraph Matching Techniques for QA systems (Exobrain) @ IITP
    2014-2016
    · Personalized Recommendation on Credit Card Benefits @ Hyundai Card
    2016
    · Personalized Recommendation on Office Social Networks @ Hancom
    2014-2015

    Talks or Guest Lectures

    · Graph Machine Learning @ Kangwon National University
    Apr. 2024
    Nov. 2023
    Oct. 2023
    · Graph Neural Networks @ Rural Development Administration
    Apr. 2022
    Jul. 2020
    Jan. 2019
    Jun. 2017
    Jul. 2016

    Patents

    Nov. 2020
    May. 2020
    Nov. 2019
    Apr. 2019
    Jan. 2019

    Teaching Experience - Instructor

    · Recommender System @ SSU
    24-1
    · Data Structure @ SSU
    24-1
    · Big Data @ SSU
    23-2
    · Software Analysis and Design @ SSU
    23-2
    · 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

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

    - Awarded by SWCU Council
    Aug. 2023

    · Jong-whi Lee, Humantech Paper Award (Bronze Prize)

    - Awarded by Samsung
    Feb. 2023

    · Jong-whi Lee, AAAI-23 Student Scholarship

    - Awarded by AAAI
    Dec. 2022

    Projects

    · Representation Learning for Mining Signed Graphs

    - Supported by NRF
    2021-Present

    · Artificial intelligence innovation hub R&D

    - Supported by IITP
    2021-Present

    · Model Compression for Deep Graph Neural Networks (SW-StarLab)

    - Supported by IITP
    2020

    · Fast Ranking in Large-scale Graphs via Link Analysis

    - Supported by NRF
    2017-2019

    · Knowledge Based News Map Generation

    - Supported by NC Soft
    2018-2019

    · Deep Learning Techniques on Graphs for QA systems (Exobrain)

    - Supported by IITP
    2017-2019

    · Event Retrieval and Mining from Unstructured Texts

    - Supported by NC Soft
    2017-2018

    · Partial Subgraph Matching Techniques for QA systems (Exobrain)

    - Supported by IITP
    2014-2016

    · Personalized Recommendation on Credit Card Benefits

    - Supported by Hyundai Card
    2016

    · Personalized Recommendation on Office Social Networks

    - Supported by Hancom
    2014-2015

    Talks or Guest Lectures

    · Graph Machine Learning

    - Talk at Kangwon National University
    2024

    · Learning Graphs with Random Walks

    - Talk at DMLAB, KAIST
    2023

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

    - Talk at KJDB 2023
    2023

    · Graph Neural Networks

    - Talk at Rural Development Administration
    2022

    · Machine Learning with Graphs

    2020

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

    - Talk at NC Soft
    2019

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

    - Talk at Korea Computer Congress
    2017

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

    - Talk at Naver Labs
    2016

    Patents

    Nov. 2020
    May. 2020
    Nov. 2019
    Apr. 2019
    Jan. 2019

    Teaching Experience - Instructor

    · Recommender System @ SSU
    24-1
    · Data Structure @ SSU
    24-1
    · Big Data @ SSU
    23-2
    · Software Analysis and Design @ SSU
    23-2
    · 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