Hsu-Chao Lai (賴旭昭)
Hsu-Chao Lai (賴旭昭)

Assistant Professor

Department of Artificial Intelligence, Chang Gung University

About Me

Dr. Hsu-Chao Lai (賴旭昭) is an Assistant Professor in the Department of Artificial Intelligence at Chang Gung University. His research focuses on recommender systems, social network analysis, and interdisciplinary data mining, with applications in healthcare, sports analytics, online platforms, and intelligent decision-making. He is also passionate about teaching data mining and graph learning, and welcomes collaborations that connect machine learning research with real-world challenges.

Solo traveler, hand-brew coffee enthusiast, and curious listener.

Download CV · Updated Sep 9, 2026
Interests
  • Recommender Systems
  • Social Network Analysis
  • Cross-domain Collaborations
Education

  • PhD in Computer Science

    National Yang Ming Chiao Tung University (NYCU)

  • Master in Computer Science

    National Chiao Tung University (NCTU)

  • BS in EECS Honor Program

    National Chiao Tung University (NCTU)

📚 Recruiting Students
  • Position: Master’s Students
  • Research Topics: Recommender Systems, Social Networks, Intelligent Decision-Making, or other Data Mining and Machine Learning topics you are passionate about
  • Preferred Skills: Python, basic machine learning, independent learning

To apply, email me with your CV, transcript, and a brief, relevant research proposal.

Recent Publications
Guan-Yi Jhang, Jeng-Chung Lien, Hsu-Chao Lai, Jiun-Long Huang (2026). SPAIT: A Novel Movement Forecasting Model with Shot-Based Position-Adaptive Inference Transformer in Badminton. Journal of Big Data.
URL DOI
Chia-Yu Huang, Hsu-Chao Lai, Yang-Che Sun, Wen-Yueh Shih, Jiun-Long Huang (2025). A Market-Aware Real-Time Bidding Strategy Using Censored Data with Reinforcement Learning in Online Advertising. 2025 IEEE International Conference on Big Data (BigData).
URL DOI
Lo Pang-Yun Ting, Ali Senol, Huan-Yang Wang, Hsu-Chao Lai, Kun-Ta Chuang, Huan Liu (2025). Towards Hierarchical Multi-Agent Decision-Making for Uncertainty-Aware EV Charging. 2025 IEEE International Conference on Big Data (BigData).
URL DOI
Lo Pang-Yun Ting, Yu-Hao Chiang, Yi-Tung Tsai, Hsu-Chao Lai, Kun-Ta Chuang (2025). DeCo: Defect-Aware Modeling with Contrasting Matching for Optimizing Task Assignment in Online IC Testing. Proceedings of the 34th International Joint Conference on Artificial Intelligence (IJCAI 2025).
URL DOI
Chih-Chao Hsu, Hsu-Chao Lai, Guan-Yi Jhang, Jiun-Long Huang, Jun-Zhe Wang (2025). NEST: A Novel Ensemble Method for Estimating Spatio-Temporal Gait Parameters Using Inertial Measurement Units. J. Artif. Intell. Soft Comput. Res..
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