School of Electrical Engineering and Computer Science (EECS)
Ohio University
Athens, Ohio, United StatesEmail:
Biography.
Research Directions. My research focuses on AI for health with an emphasis on generative AI and statistical machine learning. My vision is to build trustworthy AI models to address biomedical challenges.
- Trustworthy LLMs in healthcare: I design novel algorithms to enhance explainability, uncertainty analysis, and prediction safety for biomedical LLMs.
- Generative AI: I design time-series representation learning method for biosignals, clinical measurements, and longitudinal medical records.
- Statistical machine learning: I design probabilistic models and statistical inference for interpretable medical representations using electronic health records.
Lab Opening. We are hiring Ph.D. students and research interns interested in AI (e.g., LLMs, RL，Agents) and biomedical applications!
- Hold or be enrolled in a degree program in CS, statistics, or a closely related field.
- Have related research experience, preferably with at least one first-authored or co-first authored paper.
- Bonus: Experience applying computational methods to biomedical applications.
- We welcome both undergraduate and graduate interns from OhioU and other institutions.
Collaboration with Me. I am open to external opportunities for invited talks, research collaborations, and part-time consulting employment.
✈ News and Travel
[Aug 2025] Our TimelyGPT is accepted at journal Health Information Science and Systems.
[Aug 2025] I joined School of EECS at Ohio University as Assistant Professor.
[May 2025] I Completed my Ph.D. degree at McGill University.
[Nov 2024] Our TimelyGPT work at ACM BCB won the Risking Star Award.
[Oct 2024] TrajGPT: Irregular Time-Series Representation Learning for Health Trajectory Analysis will appear at Neurips 2024 workshop TSALM.
[Sep 2024] TimelyGPT: Extrapolatable Transformer Pre-training for Long-term Time-Series Forecasting in Healthcare will appear at ACM-BCB with oral presentation!
[Sep 2024] I present an abstract of the work at the CARTaGENE group in Scientific Meeting of the Canadian Translational Geroscience Network.
[Aug 2024] BiTimelyGPT: Bidirectional Generative Pre-training for Improving Healthcare Time-series Representation Learning published at MLHC 2024 as a poster paper!
[Apr 2024] I present a tutorial of my KDD work MixEHR-Seed in Workshop - Genomic Medicine, Therapeutics and Health.
[May 2023] I present an abstract of MixEHR-SAGE work in ISMB GLBIO 2023.
[Apr 2023] I receive financial support from Quebec Government via Quebec Doctoral Scholarship (FRQNT) !
[May 2022] MixEHR-Seed: Automatic phenotyping by a seed-guided topic model published at KDD and won health day best paper award!
🏅 Honors and Awards
As Ph.D.
- Quebec Doctoral Scholarship FRQNT, 2023
- Faculty of Science Grad Supplement Award, 2022
- Jackie Cheung Graduate Award, 2020
- SOCS Grad Stimulus Initiative Award, 2020
- Grad Excellence Award in Computer Science, 2020
- McGill PhD Stipend, 2020