Y. Samuel Wang

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)