Yuming Sun

Yuming Sun is an Assistant Professor in the Department of Mathematics at the College of William & Mary. His work bridges statistical methodology and applications in biomedical and public health domains, with a strong emphasis on developing robust models for complex health data.

Dr. Sun's research focuses on statistical learning, survival analysis, causal inference, and non-/semi-parametric modeling. He applies these methods to clinical datasets, electronic health records, and medical images, contributing to predictive analytics in healthcare. His work often involves high-dimensional and longitudinal data, requiring innovative integration of traditional statistics with modern machine learning.

The recent publications reflect a consistent trend toward integrating deep learning with classical survival models, especially in medical imaging and environmental health contexts. His research spans prognostic modeling for diseases like COVID-19 and assessing population-level responses to environmental stressors such as wildfires and air pollution.

While no formal scientific awards are listed in the provided text, his active research output and software development indicate strong scholarly engagement.

Dr. Sun advises graduate students in statistics and biostatistics, though specific names are not listed. His research is likely supported by grants related to health data science, though specific funding sources are not mentioned. He maintains an active presence in open science through GitHub, sharing code and analyses.

He is involved in research teams or labs focused on biomedical data science, possibly within or affiliated with the Department of Mathematics, where he develops computational tools for health applications.