معرفی
Y. Samuel Wang is an Assistant Professor in the Department of Statistics and Data Science at Cornell University. He holds a PhD in Statistics from the University of Washington and a BS in Applied Mathematics and Economics from Rice University. Prior to academia, he worked as a management consultant and served as a postdoctoral researcher at the University of Chicago’s Booth School of Business. His research focuses on causal discovery, graphical models, mixed membership models, and high-dimensional data analysis, with applications in network science, environmental studies, and healthcare.
Education:
- PhD in Statistics, University of Washington
- BS in Applied Mathematics & Economics, Rice University
Research Interests:
- Development of interpretable statistical methods for causal inference and graphical model structures
- High-dimensional data analysis, particularly in non-Gaussian settings
- Applications in collaborative networks, environmental microbiology, and healthcare outcomes
Recent Research Trends: Recent publications emphasize causal discovery under latent confounding, functional graphical models, and gender dynamics in scholarly collaborations. Methodological contributions include robust high-dimensional inference techniques and computational tools for cyclic structural equation models.
Professional Activity:
- Licensed on GitHub, Google Scholar, and ORCID
- GitHub repositories include projects on causal discovery (highDNG), gender homophily analysis (genderHomophily), and mixed membership models (mixedMem)
