Recent Ph.D. Dissertations

Department of Statistics – Academic Commons Link to Recent Ph.D. Dissertations (2011 – present)

2022 Ph.D. Dissertations

      1. Andrew Davison

        Statistical Perspectives on Modern Network Embedding Methods

        Sponsor: Tian Zheng

      2. Nabarun Deb

        Blessing of Dependence and Distribution-Freeness in Statistical Hypothesis Testing

        Sponsor: Bodhisattva Sen / Co-Sponsor: Sumit Mukherjee

      3. Elliot Gordon Rodriguez

        Advances in Machine Learning for Compositional Data

        Sponsor: John Cunningham

      4. Charles Christopher Margossian

        Modernizing Markov Chains Monte Carlo for Scientific and Bayesian Modeling

        Sponsor: Andrew Gelman

      5. Alejandra Quintos Lima

        Dissertation TBA

        Sponsor: Philip Protter

      6. Bridgette Lynn Ratcliffe

        Statistical approach to tagging stellar birth groups in the Milky Way

        Sponsor: Bodhisattva Sen

      7. Chengliang Tang

        Dissertation TBA

        Sponsor: Tian Zheng

      8. Owen Ward

        Latent Variable Models for Events on Social Networks

        Sponsor: Tian Zheng

      9. Shun Xu

        On Recovering the Best Rank-? Approximation from Few Entries

        Sponsor: Ming Yuan

      10. Yuanzhe Xu

        Dissertation TBA

        Sponsor: Sumit Mukherjee

2021 Ph.D. Dissertations

      1. Tong Li

        On the Construction of Minimax Optimal Nonparametric Tests with Kernel Embedding Methods

        Sponsor: Liam Paninski

      2. Ding Zhou

        Advances in Statistical Machine Learning Methods for Neural Data Science

        Sponsor: Liam Paninski

      3. Milad Bakhshizadeh

        Phase retrieval in the high-dimensional regime

        Sponsor: Arian Maleki

      4. Chi Wing Chu

        Semiparametric Inference of Censored Data with Time-dependent Covariates

        Sponsor: Zhiliang Ying

      5. Miguel Angel Garrido Garcia

        Characterization of the Fluctuations in a Symmetric Ensemble of Rank-Based Interacting Particles

        Sponsor: Ioannis Karatzas

      6. Rishabh Dudeja

        High-dimensional Asymptotics for Phase Retrieval with Structured Sensing Matrices

        Sponsor: Arian Maleki

      7. Zhi Wang

        Statistical Learning for Process Data

        Sponsor: Jingchen Liu

      8. Yuling Yao

        Toward a scalable Bayesian workflow

        Sponsor: Andrew Gelman

2020 Ph.D. Dissertations

      1. Jonathan Auerbach

        Some Statistical Models for Prediction

        Sponsor: Shaw-Hwa Lo

      2. Adji Bousso Dieng

        Deep Probabilistic Graphical Modeling

        Sponsor: David Blei

      3. Guanhua Fang

        Latent Variable Models in Measurement: Theory and Application

        Sponsor: Zhiliang Ying

      4. Promit Ghosal

        Time Evolution of the Kardar-Parisi-Zhang Equation

        Sponsor: Ivan Corwin

      5. Lydia Hsu

        Partition-based Model Representation Learning

        Sponsor: Shaw-Hwa Lo

      6. Sihan Huang

        Community Detection in Social Networks: Multilayer Networks and Pairwise Covariates

        Sponsor: Zhiliang Ying

      7. Peter JinHyung Lee

        Spike Sorting for Large-scale Multi-electrode Array Recordings in Primate Retina

        Sponsor: Liam Paninski

      8. Brian Ling

        Statistical Analysis of Complex Data in Survival and Event History Analysis

        Sponsor: Zhiliang Ying

      9. Yixin Wang

        Multiple Causal Inference with Bayesian Factor Models

        Sponsor: David Blei

      10. Wenda Zhou

        New perspectives in cross-validation

        Sponsor: Arian Maleki

        Link to PhD Dissertations on Academic Commons