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Statistics PhD Alumni

2022 PhD Alumni

Hamid Eftekhari

Advisor: Ya'acov Ritov and Moulinath Banerjee

Dissertation: c-Optimal Designs in High-dimensional Linear Models

Last Known Position: Data Scientist, Google


Sanjana Gupta

Advisor: Kerby Shedden

Dissertation: Contributions to nonparametric quantile analysis and quantile-based mediation analysis, with applications to lifecourse analysis in human biology 

Last Known Position: Quantitative Research, Virtu Financial


Byoungwook Jang

Advisor: Alfred Hero

Dissertation: Probabilistic Decomposition in Machine Learning Problems

Last Known Position: Research Scientist, Meta


Caleb Ki

Advisor: Edward Ionides

Dissertation: Statistical Methods in Population Genetics and Viral Phylodynamics

Last Known Position: Data Scientist, Lyft


Michael Law

Advisor: Ya'acov Ritov

Dissertation: Investigations in Ultra High-Dimensional Models

Last Known Position: Unknown


Rayleigh Lei

Advisor: Long Nguyen

Dissertation: Modeling Simplex-valued Data and Latent Structures

Last Known Position: Postdoc, University of Washington


Chengcheng Li

Advisor: Gongjun Xu

Dissertation:  Statistical Estimation and Inference for Large-Scale Categorical Data

Last Known Position: Applied and Data Scientist, Microsoft


Yuanzhi Li

Advisor: Xuming He

Dissertation: Contributions to Quantile and Superquantile Regression

Last Known Position: Quantitative Researcher, Five Rings Capital


Yangyi Lu

Advisor: Liza Levina

Dissertation: Advances in Sequential Decision Making Problems with Causal and Low-Rank Structures

Last Known Position: Machine Learning Engineer, Pinterest


Timothy Lycurgus

Advisor: Ben B. Hansen

Dissertation: Dry runs and PWRD aggregation: Two new methods for extracting power from careful observation of a field experiment's context

Last Known Position: Postdoctoral Research Assistant


Chenchen Ma

Advisor: Gongjun Xu

Dissertation: Statistical Learning for Latent Attribute Models

Last Known Position: Unknown


Debarghya Mukherjee

Advisor: Ya'acov Ritov and Moulinath Banerjee

Dissertation: Estimation of a score-explained non-randomized treatment effect in fixed and high dimensions

Last Known Position: Unknown


Laura Niss

Advisor: Ambuj Tewari and Yuekai Sun

Dissertation: Topics in Sequential Decision Making and Algorithmic Fairness

Last Known Position: Unknown


Nora Payne

Advisor: Johann Gagnon-Bartsch

Dissertation: An Accurate and Scalable Approach to Classifying High-Dimensional Data With Dense Latent Structure

Last Known Position: Unknown


Zoe Rehnberg

Advisor: Johann Gagnon-Bartsch

Dissertation: Robust and Computationally Efficient Methods for High-Throughput Drug Screening Studies

Last Known Position: Assistant Professor, California Polytechnic State Univiersity


Weijing Tang

Advisor: Ji Zhu

Dissertation: Statistical Learning for Large-Scale and Complex-Structured Data

Last Known Position: Assistant Professor, Carnegie Mellon University


Yu Wang

Advisor: Alfred Hero and Yang Chen

Dissertation: Interpretable and Scalable Graphical Models for Complex Spatio-temporal Processes

Last Known Position: Unknown


Andrew Yarger

Advisor: Tailen Hsing and Stilian Stoev

Dissertation: Statistical approaches for spatially-dependent functional data and their application in oceanography

Last Known Position: Postdoctoral Appointee, Sandia National Laboratories

2021 PhD Alumni

Kidus Asfaw

Advisor: Ed Ionides

Dissertation: Simulation-based Inference for Partially Observed Markov Process Models with Spatial Coupling

Last Known Position: Data Scientist, Microsoft


Baekjin Kim 

Advisor: Ambuj Tewari

Dissertation: Random Perturbations in Stochastic Bandit Problems

Last Known Position: Machine Learning Engineer, Twitter


Edward Wu

Advisor: Johann Gagnon-Bartsch

Dissertation: Design-Based Methods for the Analysis of Modern Randomized Experiments

Last Known Position: Science Policy Fellow, American Statistical Assosciation 


Nicholas Seewald

Advisor: Daniel Almirall and Kerby Shedden

Dissertation: Design and Analytic Considerations for Sequential, Multiple-Assignment Randomized Trials with Longitudinal Outcomes 

Last Known Position: Postdoctoral Fellow Department of Health Policy and Management, Johns Hopkins Bloomberg School of Public Health


Yinqiu He

Advisor: Gongjun Xu and Xuming He

Dissertation: High-Dimensional Statistical Inference: Phase Transition, Power Enhancement, and Sampling

Last Known Position: Postdoctoral Research Scientist, Columbia University - Data Science Institute

2020 PhD Alumni

Anwesha Bhattacharyya
Advisor: Yves Atchade
Dissertation: An Approach to Large-Scake Quasi-Bayesian Inference With Spike-and-Slab Priors
Last Known Position: Quantitative Analytics Specialist, Wells Fargo

April Cho
Advisor: Gongjun Xu
Dissertation: Gaussian Variational Estimation for Multidimensional Item Response Theory
Last Known Position: Data Scientist/Research Analyst, CNA Corporation

Joseph Dickens
Advisor: Kerby Shedden
Dissertation: Contributions to mediation analysis and first principles modeling for mechanistic statistical analysis
Last Known Position: Research Fellow, University of Michigan School of Public Health

Robyn Ferg
Advisor: Johann Gagnon-Bartsch
Dissertation: Consumer Confidence and Political Polarization using Twitter
Last Known Position: Statistician, Westat - Improving Lives Through Research

Zheng Gao
Advisor: Stillian Stoev
Dissertation: On the Fundamental Limits in High-dimensional Testing and Inference
Last Known Position: Unknown

Jack Goetz
Advisor: Ambuj Tewari
Dissertation: Active Learning in Non-parametric and Federated Settings
Last Known Position: Research Scientist, Meta

Aritra Guha
Advisor: Long Nguyen
Dissertation: Inference and interpretability in latent variable modeling
Last Known Position: Senior Inventive Scientist, AT&T Labs, Inc.

Yumu Liu
Advisor: Ji Zhu
Dissertation: Statistical Methods for Networks with Node Covariates
Last Known Position: Data Scientist, Google

Brook Luers
Advisor: Kerby Shedden
Dissertation: Improved Performance and Stability of the Knockoff Filter and an Approach to Mixed Effects Modeling of Sequentially Randomized Trials
Last Known Position: Data Scientist, Google

Yuan Sun
Advisor: Xuming He
Dissertation: On Rank-Based Inference for Quantile Regression
Last Known Position: Unknown

Hyesun Yoo
Advisor: Ji Zhu
Dissertation: Statistical Tools for Directed Networks and Bipartite Networks
Last Known Position: Data Scientist, Google