After 2024 Ph.D. Dissertations

Bayesian Inference for Exponential-family Random Graph Models

Joseph Resch; Ph.D., 2026

Causal Discovery for Dependent Binary and Mixed Data

Alex Chen; Ph.D., 2026

Membership Inference Attacks Against Tabular Synthetic Data Under Conservative Threat Models

Joshua Ward; Ph.D., 2026

Nonlinear Causal Discovery via Sequential Edge Orientation for Directed Acyclic Graphs and Mixed Graphs

Stella Huang; Ph.D., 2026

Sequential Learning and Inference of Causal Graphical Models

Yijia Zhao; Ph.D., 2026

Statistical Methods for Complex Biomedical Data: From Bayesian Changepoint Detection to Machine Learning Applications

Vincent Liu; Ph.D., 2026

Three Practical Challenges in Causal Inference and Straightforward Solutions

Tanvi Shinkre; Ph.D., 2025