Machine Learning · Statistical Modeling · Large-scale Multi-modal Data
M.S. in Biostatistics (Data Science Track) at Yale University
I am a Master’s student in Biostatistics (Data Science track) at Yale University, where I work with Dr. Yize Zhao at the Yale School of Public Health. I earned my Honor B.S. in Computer Science and Statistics (with high distinction, minor in Mathematics) at the University of Toronto. My research lies at the intersection of machine learning, statistical modeling, and large-scale, multi-modal complex data. I develop interpretable and scalable statistical and machine-learning methods for high-dimensional and structured data, with particular interests in Bayesian modeling, statistical neuroimaging and brain connectivity, disease-network and hypergraph modeling for longitudinal health data(EHR), multilingual NLP and LLM evaluation, and large-scale retrieval systems(RAG).
Statistical and computational methods for structure–function (SC–FC) coupling in brain networks, including orthogonal sparse subgraph alignment and identifiability studies on the ABCD study.
View on Research page →
Bayesian models for multimorbidity, latent disease pathways, and survival in longitudinal EHR data.
View on Research page →
Large-scale benchmarks and datasets for topic classification, sentence simplification, and math word problem generation across 200+ languages and low-resource settings.
View on Research page →
End-to-end LLM–RAG systems over 2TB+ of heterogeneous financial text, with multi-stage semantic retrieval, temporal constraints, and high-throughput batched serving.
View on Research page →Background
M.S.
Biostatistics · Data Science Track
Yale University
New Haven, CT, USA
Sep 2024 – May 2026
Honor B.S. · High Distinction
Computer Science & Statistics, Mathematics
University of Toronto
Toronto, ON, Canada
Sep 2019 – May 2024