Curriculum Vitae
Research profile, training, and recent milestones
Sihang Zeng develops AI methods for longitudinal electronic health records, with a focus on patient trajectory modeling, clinical foundation models, and trustworthy decision support.
Education
University of Washington
Advised by Ruth Etzioni and Meliha Yetisgen. Committee includes Hoifung Poon, Matthew Thompson, and Noemi Kreif.
Tsinghua University
Built the foundations for later work in biomedical representation learning and AI for healthcare.
Experience
Truveta
Worked on foundation-model ideas over large-scale de-identified clinical data for disease trajectory and screening applications.
University of Washington
Researching longitudinal EHR modeling, clinical decision support, and evaluation methods for biomedical AI.
Tsinghua University
Focused on biomedical term and knowledge representation, bridging NLP infrastructure with downstream biomedical reasoning.
Selected honors
- 1st Place, ChemoTimelines 2025 Challenge
- NeurIPS 2024 Datasets and Benchmarks Spotlight for UltraMedical