Kanghoon Yoon

Kanghoon Yoon

AI Engineer, Huawei Research · Singapore

I am an AI Engineer at the Huawei Research Center in Singapore, where I joined the Audio & Video Algorithm Team in November 2025.

I earned my Ph.D. from KAIST in August 2025 under the guidance of Associate Professor, Chanyoung Park, at the Data Science and Artificial Intelligence Lab (DSAIL).

My research portfolio spans Scene Understanding, Multi-modal Foundation model, and Embodied AI with a strong focus on optimizing AI inference efficiency and advancing representation learning. I am also deeply invested in enhancing the security of deep learning through research on adversarial attacks and robustness.

I am always open to insightful discussions and potential collaborations. Feel free to reach out to me via email at ykhoon0827@gmail.com or through LinkedIn.

News

  • My first-author paper got accepted at ICML 2026
  • A paper got accepted at ICLR 2026
  • I joined Huawei Singapore Research Center as AI Engineer
  • A paper got accepted at NeurIPS 2025
  • A paper got accepted at EMNLP 2025 (Findings)
  • I received Ph.D at KAIST!
  • I completed my Ph.D dissertation!
  • Started internship at Naver Cloud
  • A paper got accepted at ICLR 2025
  • My first-author paper got accepted at AAAI 2025
  • A paper got accepted at WSDM 2025
  • A paper got accepted at CIKM 2024
  • A paper got accepted at ECCV 2024
  • I joined Qualcomm AI (San Diego) as an internship

Education

  • KAIST — Ph.D Dept. of Industrial and Systems Engineering
  • KAIST — M.S Dept. of Industrial and Systems Engineering
  • Hanyang University — B.S Mathematics

Work Experience

  • Huawei Research — AI Engineer Singapore · Dec 2025 – Present
  • Naver Cloud — Research Intern Republic of Korea · Feb – Aug 2025
  • Qualcomm AI — Research Intern San Diego · Jun – Sep 2024

Academic Services

  • International Conference Area Chair KDD (2026-Cycle2)
  • International Conference Reviewer NeurIPS (2025), ICLR (2026), ICML (2026), CVPR (2026), AAAI (2024, 2025, 2026), KDD (2024, 2025-1, 2025-2, 2026-1)
  • International Journal Reviewer ACM Knowledge Discovery from Data (2024), TPAMI (2024, 2025)

Invited Talks

  • Korea Software Congress Talk at the top conference session
  • Korea Computer Congress Talk at the top conference session