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

From Subjective to Principled Single-Cell Data Analysis: Evaluating Annotation Behavior, Optimizing Integration, and Benchmarking Visualization Pipelines

Zhiqian Zhai; Ph.D., 2026

Improving Power and Uncertainty Quantification in Spatiotemporal Climate Applications

Kyle Roberts McEvoy; Ph.D., 2026

Membership Inference Attacks Against Tabular Synthetic Data Under Conservative Threat Models

Joshua Ward; Ph.D., 2026

Modeling and Estimation of Variable Productivity Models for Infectious Diseases

Sophie Phillips; 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

Advancing Bayesian Forecasting: A Bayesian Dirichlet Auto-Regressive Conditional Heteroskedasticity Model, a Bayesian Dirichlet Auto-Regressive Moving Average Model, and Other Innovations

Harrison Katz; Ph.D., 2025

Advancing Statistical Rigor in Single-Cell and Spatial Omics Analysis Through In Silico Control Data

Guanao Yan; Ph.D., 2025

Applications of synthetic null controls to enhance omics data analysis, from gene expression to sequences

Christy Lee; Ph.D., 2025

Deep Learning Methodology and Theoretical Analysis for Change Points, Spatiotemporal and Contaminated Data

Jialiang Geng; Ph.D., 2025

Deep Learning of Discriminative Gene Expression Models and Generative Models of Molecule and Protein Sequences

Edouardo Honig; Ph.D., 2025

Enhancing the Reasoning Capabilities of Large Language Models: From Game Playing to Embodied Planning

Shu Wang; Ph.D., 2025

Generalizable 3D Understanding and Generation

Chao Xu; Ph.D., 2025

Graph-Informed Sequential Decision Making

Shuang Wu; Ph.D., 2025

Latent Space Modeling for Brain Mechanisms, Language and Decision-Making

Dehong Xu; Ph.D., 2025

Locally Adaptive Statistical Models with Applications in Quantile Regression and Causal Inference

Siwei Ye; Ph.D., 2025

Structure, Symmetry, and Singularity in Learning Systems

Jiayi Li; Ph.D., 2025

Three Practical Challenges in Causal Inference and Straightforward Solutions

Tanvi Shinkre; Ph.D., 2025

Uncertainty Quantification in Structured High Dimensional Regression Tasks with Missing Data

Nathan Hwangbo; Ph.D., 2025

Unsupervised Methods on Structured Data

Luciano Vinas; Ph.D., 2025