Thomas Lai 賴正惟

PhD Student at McGill University in deep learning, time-series, foundation models, and anomaly detection.

Publications

  • *T. Lai, *T. K. K. Ho, P. Klimes, J. Cimbalnik, M. Pail, M. Brazdil, B. Frauscher, and N. Armanfard, “Foundation Models for Epileptogenic Zone Identification in Drug-Resistant Epilepsy,” arXiv preprint arXiv:2606.22657, Jun. 2026. doi: https://doi.org/10.48550/arXiv.2606.22657. (*Equal Contribution)
  • T. Lai, T. K. K. Ho, and N. Armanfard, “Open-Set Multivariate Time-Series Anomaly Detection,” in Frontiers in Artificial Intelligence and Applications Volume 392: ECAI 2024, IOS Press, Oct. 2024, pp. 2003–2010. doi: https://doi.org/10.3233/faia240716.

Experience

  • Research Assistant Intern @ McGill ECE (2023)
  • Biomanufacturing Intern @ National Research Council Canada (2022)
  • Research Assistant Intern @ Michael Smith Laboratories UBC (2020-2021)
  • Lifeguard/Swim Instructor @ City of Burnaby (2018-2019)

Awards

  • NSERC PGS-D (Canadian Federal Doctoral Research Award) 2025-2028
  • Vadasz Fellowship (McGill Engineering Doctoral Entrance Fellowship) 2024-2028
  • NSERC CGS-M (Canadian Federal Master’s Research Award) 2024-2025
  • FRQNT-Master’s (Quebec Provincial Master’s Research Award) 2024-2025
  • MEUSMA (McGill Engineering Master’s Entrance Scholarship) 2023-2024
  • NSERC USRA (Canadian Federal Undergraduate Research Award) 2021
  • GHD Memorial Scholarship (McGill Undergraduate Entrance Scholarship) 2018-2023

Academic and Community Service

  • Workshop organizer and paper reviewer for the 2nd Workshop on Automated Spatial and Temporal Anomaly Detection (ASTAD) @ WACV 2025
  • Paper reviewer for the 3rd Workshop on Automated Spatial and Temporal Anomaly Detection (ASTAD) @ AAAI 2026
  • Workshop organizer for the upcoming 4th Workshop on Automated Spatial and Temporal Anomaly Detection (ASTAD)
  • Paper review contribution under the supervision of Prof. Armanfard for AAAI 2027, CVPR 2026, IJCAI 2025, NeurIPS 2025, WACV 2027
  • Paper reviewer for Foundation Models for Temporal Systems (FMTS) @ NeurIPS 2026
  • Volunteering team leader for Discover McGill 2024
  • Tour guide for Graduate Campus Tours 2024
  • Modeling team lead for McGill iGEM design team 2020-2022
  • First responder for McGill Student Emergency Response Team 2018-2020

Skills and Interests

Python, Git, Bash, Unix, MATLAB, R, Deep learning, Time series, Signal Processing, Foundation models, EEG analysis for Epilepsy, Anomaly detection, Reinforcement Learning, Music Production, Audio Engineering, French, Mandarin, Hokkien, Spanish, Japanese.