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D-Index & Metrics

Computer Science

D-Index
58
Citations
18195
World Ranking
3559
National Ranking
475

Overview

Sunghun Kim is affiliated with the Hong Kong University of Science and Technology in China. The primary research focus lies within the field of Computer Science, with significant contributions to subfields such as Artificial Intelligence, Information Systems, Social Psychology, Radiology, Nuclear Medicine and Imaging, and Nutrition and Dietetics.

The scientist's research interests cover several main topics, including:

  • Recommender Systems and Techniques
  • Advanced Graph Neural Networks
  • Color perception and design
  • Mental Health via Writing
  • Machine Learning in Healthcare
  • Nutrition, Health and Food Behavior
  • Functional Brain Connectivity Studies

Frequent publication venues for Sunghun Kim include:

  • arXiv (Cornell University)
  • Journal of the Korean society for Wellness
  • Foods
  • PLoS ONE
  • Economies

Recent papers authored or co-authored by Sunghun Kim are:

  • "A Survey on Large Language Models for Code Generation," 2024, arXiv (Cornell University)
  • "Efficiently Leveraging Multi-level User Intent for Session-based Recommendation via Atten-Mixer Network," 2022, arXiv (Cornell University)
  • "Superfine Marigold Powder Improves the Quality of Sponge Cake: Lutein Fortification, Texture, and Sensory Properties," 2023, Foods
  • "ClovaCall: Korean Goal-Oriented Dialog Speech Corpus for Automatic Speech Recognition of Contact Centers," 2020, arXiv (Cornell University)
  • "A Survey on Incremental Update for Neural Recommender Systems," 2023, arXiv (Cornell University)

Collaborators frequently working with Sunghun Kim include:

  • Yueqi Xie
  • Peiyan Zhang
  • Xing Xie
  • Chaozhuo Li
  • Peilin Zhou

Best Publications

  • StarGAN: Unified Generative Adversarial Networks for Multi-domain Image-to-Image Translation

    Yunjey Choi;Minje Choi;Munyoung Kim;Jung-Woo Ha

  • Classifying Software Changes: Clean or Buggy?

    Sunghun Kim;E.J. Whitehead;Yi Zhang

  • Predicting Faults from Cached History

    Sunghun Kim;T. Zimmermann;E.J. Whitehead;A. Zeller

  • Improving bug triage with bug tossing graphs

    Gaeul Jeong;Sunghun Kim;Thomas Zimmermann

  • Automatic patch generation learned from human-written patches

    Dongsun Kim;Jaechang Nam;Jaewoo Song;Sunghun Kim

  • Deep API learning

    Xiaodong Gu;Hongyu Zhang;Dongmei Zhang;Sunghun Kim

  • Deep code search

    Xiaodong Gu;Hongyu Zhang;Sunghun Kim

  • Automatically patching errors in deployed software

    Jeff H. Perkins;Sunghun Kim;Sam Larsen;Saman Amarasinghe

  • ReLink: recovering links between bugs and changes

    Rongxin Wu;Hongyu Zhang;Sunghun Kim;Shing-Chi Cheung

  • Heterogeneous Defect Prediction

    Jaechang Nam;Wei Fu;Sunghun Kim;Tim Menzies

  • Transfer defect learning

    Jaechang Nam;Sinno Jialin Pan;Sunghun Kim

  • Automatic Identification of Bug-Introducing Changes

    Sunghun Kim;T. Zimmermann;Kai Pan;E.J. Whitehead

  • Dealing with noise in defect prediction

    Sunghun Kim;Hongyu Zhang;Rongxin Wu;Liang Gong

  • Heterogeneous defect prediction

    Jaechang Nam;Sunghun Kim

  • Duplicate bug reports considered harmful … really?

    N. Bettenburg;R. Premraj;T. Zimmermann;Sunghun Kim

  • Toward an understanding of bug fix patterns

    Kai Pan;Sunghun Kim;E. James Whitehead

  • Reducing Features to Improve Code Change-Based Bug Prediction

    S. Shivaji;E. James Whitehead;R. Akella;Sunghun Kim

  • Personalized defect prediction

    Tian Jiang;Lin Tan;Sunghun Kim

  • Which warnings should I fix first

    Sunghun Kim;Michael D. Ernst

  • CLAMI: Defect Prediction on Unlabeled Datasets (T)

    Jaechang Nam;Sunghun Kim

  • Predicting faults from cached history

    Sunghun Kim;Thomas Zimmermann;E. James Whitehead;Andreas Zeller

Frequent Co-Authors

Thomas Zimmermann
Thomas Zimmermann Microsoft (United States)
Hongyu Zhang
Hongyu Zhang Chongqing University
Michael D. Ernst
Michael D. Ernst University of Washington
Andreas Zeller
Andreas Zeller Saarland University
Shing-Chi Cheung
Shing-Chi Cheung Hong Kong University of Science and Technology
Dongmei Zhang
Dongmei Zhang Microsoft (United States)
Jaegul Choo
Jaegul Choo Korea Advanced Institute of Science and Technology
Miryung Kim
Miryung Kim University of California, Los Angeles
Tao Xie
Tao Xie Peking University
Audris Mockus
Audris Mockus University of Tennessee at Knoxville

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