Statistics PhD Alumni

Yichao Chen

Advisor: Ji Zhu

Dissertation: Statistical Modeling for Structured Network and Functional Data

Last Known Position: Research Advisor - Statistics, Eli Lilly & Co

Alexander Kagan

Advisors: Liza Levina & Ji Zhu

Dissertation: Accounting for Heterogeneity in Statistical Models of Network Data

Last Known Position: Postdoctoral Fellow - Biostatistics, Yale University

Yang Li

Advisor: Ji Zhu

Dissertation: Structured Statistical Learning and Inference for Complex Scientific Data

Last Known Position: Quantitative Researcher, Cubist Systematic Strategies

Felipe Maia Polo

Advisors: Moulinath Banerjee & Yuekai Sun

Dissertation: Principled Evaluation of Large Language Models: A Statistical Perspective

Last Known Position: Research Scientist, MIT-IBM Watson AI Lab

Eduardo Ochoa Rivera

Advisor: Ambuj Tewari

Dissertation: Statistical Foundations for Microplastic Identification: Efficient Sampling and Distribution-Free Uncertainty Quantification

Last Known Position: Quantitative Analytics Program CM PhD, Wells Fargo

Benjamin Osafo Agyare

Advisor: Kerby Shedden

Dissertation: Distributional Learning via Flexible Expectile Regression: Methods for Dependent, Multivariate and Incomplete Data

Last Known Position: Data Scientist, JP Morgan Chase

Gang Qiao

Advisor: Ambuj Tewari

Dissertation: Topics in Modern Machine Learning: Sequential Decision Making, High-Dimensional Statistics and Differential Privacy

Last Known Position: Quantitative Researcher, Point72 Ventures

Vinod Raman

Advisor: Ambuj Tewari

Dissertation: Topics in Learning Theory: Prediction, Estimation, and Partial Information

Last Known Position: Research Scientist, Google DeepMind

Seamus Somerstep

Advisors: Ya'acov Ritov & Yuekai Sun

Dissertation: A Statistical and Practical Study of Deploying Fair, Safe, and Productive AI

Last Known Position: Quantitative Researcher, Goldman Sachs

Unique Subedi

Advisor: Ambuj Tewari

Dissertation: Learning Theory in the AI for Science Era: From Classical Foundations to Operator Learning

Last Known Position: Technical Staff Member - Research, Fireworks AI

Jacob Trauger

Advisor: Ambuj Tewari

Dissertation: Topics on the Generalization and Learnability of Modern Machine Learning

Last Known Position: Graduate Machine Learning Researcher, IMC Trading

Junting Wang

Advisors: Kean Ming Tan & Ji Zhu

Dissertation: Statistical Methods for Brain Connectivity and Dynamic fMRI Analysis

Last Known Position: Data Scientist - Research, Google

Xinhe Wang

Advisor: Ben Hansen

Dissertation: Design-Based Causal Inference for Clustered Randomized Experiments and Observational Studies

Last Known Position: Data Scientist, Google

Josh Wasserman

Advisor: Ben Hansen

Dissertation: Methods for Causal Inference in Settings with Clustered Data Subject to Missingness and Measurement Error

Last Known Position: Statistician, Genentech

Kevin Wibisono

Advisor: Yixin Wang

Dissertation: Modeling Structure in Unstructured Data: Statistical and Causal Perspectives

Last Known Position: Machine Learning Scientist II, Wayfair

Shihao Wu

Advisors: Gongjun Xu & Ji Zhu

Dissertation: Efficient Embedding and Generative Modeling of Hypergraphs

Last Known Position: Assistant Professor - Statistics, University of California at Davis

Yidan Xu

Advisors: Long Nguyen & Yixin Wang

Dissertation: Transport-Based Methods for Inference and Generation with Graphical Structure

Last Known Position: Machine Learning Research Scientist, Meta

Shushu Zhang

Advisors: Kean Ming Tan & Xuming He (WUSTL)

Dissertation: Contributions to Expected Shortfall Regression

Last Known Position: Quantitative Researcher, Point72 Ventures

Yilei Zhang

Advisor: Long Nguyen

Dissertation: Bayesian Generative Modeling of Latent Subpopulations with Nonparametric Distributions

Last Known Position: Postdoctoral Fellow, UM Kellogg Eye Center

Sunrit Chakraborty

Advisor: Long Nguyen

Dissertation: Exploring Interpretable Latent Structure in Modern Data by Bayesian Modeling: Theory and Applications

Last Known Position: Postdoctoral Fellow, Duke University

Prayag Chatha

Advisors: Jeff Regier & Jon Zelner (Epidemiology)

Dissertation: Mechanistic Modeling of Complex Health Problems with Deep Learning

Last Known Position: Postdoctoral Fellow, University of Michigan at Ann Arbor

Pramit Das

Advisors: Moulinath Banerjee & Yuekai Sun

Dissertation: Generative Machine Learning, Granger Causality, and Optimal Intervention in Self-Exciting Spatiotemporal Processes

Last Known Position: Revenue Management & Operation Research Analyst, American Airlines

Trong Dat Do

Advisors: Long Nguyen & Jonathan Terhorst

Dissertation: Mixture and Admixture Models: Estimation Rate, Model Selection, Interpretation, and Applications in Heterogeneous Data Analysis

Last Known Position: William H. Kruskal Instructor, University of Chicago

Kihyuk Hong

Advisor: Ambuj Tewari

Dissertation: Theoretical Advances in Reinforcement Learning: Online Average-Reward and Offline Constrained Settings

Last Known Position: Assistant Professor, Korea Advanced Institute of Science & Technology

Easton Huch

Advisors: Fred Feinberg & Walter Dempsey (Biostatistics)

Dissertation: Robust Methods for Causal Inference and Policy Learning with Applications to Mobile Health

Last Known Position: Postdoctoral Fellow, Johns Hopkins University

Roman Kouznetsov

Advisor: Jeff Regier

Dissertation: Statistical Inference for Spatial Transcriptomics in the Age of Deep Learning

Last Known Position: Senior Risk Management Consultant, Ernst & Young

Declan McNamara

Advisor: Jeff Regier

Dissertation: Advances in Amortized Bayesian Inference, with Applications to Astronomy

Last Known Position: Associate, BMO Capital Markets

Bo Meng

Advisors: Gongjun Xu & Ji Zhu

Dissertation: Statistical Learning for Recurrent Event and Complex Network Data

Last Known Position: Quantitative Researcher, Jump Trading LLC

Yash Patel

Advisor: Ambuj Tewari

Dissertation: Conformally Robust Decision Making

Last Known Position: Research Engineer, Harmonic

Yumeng Wang

Advisor: Snigdha Panigrahi, Xuming He (WUSTL)

Dissertation: Contributions to Distributed Learning and Selective Inference

Last Known Position: Data Scientist, The Trade Desk

Jesse Wheeler

Advisor: Ed Ionides

Dissertation: Innovations in Likelihood-Based Inference for State Space Models

Last Known Position: Assistant Professor, Idaho State University

Simon Fontaine

Advisors: Ji Zhu & Jian Kang (Biostatistics)

Dissertation: Statistical Models for Dependent Data

Last Known Position: Postdoctoral Fellow, Pennsylvania State University

Yanxin Jin

Advisor: Kean Ming Tan

Dissertation: Unsupervised Learning Approaches for Large-scale Data

Last Known Position: Research Scientist, Apple

Moritz Korte-Stapff

Advisor: Tailen Hsing and Stilian Stoev

Dissertation: Statistical Modelling of Spatially and Spatio-Temporally Dependent Data: Some Theoretical Results and an Application

Last Known Position: Senior Analyst, Oliver Wyman

Jinming Li

Advisors: Gongjun Xu & Ji Zhu 

Dissertation: Statistical Learning and Inference for Network Data via Latent Space Models

Last Known Position: Quantitative Researcher, Susquehanna International Group

Vincenzo Loffredo

Advisor: Long Nguyen

Dissertation: Bayesian Perspectives on LongROAD Study: Analyzing Driving Decline and Latent Traits

Last Known Position: Business Consultant, University of Michigan Health System (Michigan Medicine)

Cheng Ma

Advisor: Ji Zhu

Dissertation: Statistical Latent Space Models for International Classification of Diseases (ICD) Codes 

Last Known Position: Quantitative Researcher, Sunrise Futures LLC

Subha Maity

Advisors: Mouli Banerjee & Yuekai Sun

Dissertation: An Exploration of the Statistical Challenges and Fairness Implications of Transfer Learning 

Last Known Position: Assistant Professor, University of Waterloo

Rebeka Man

Advisor: Kean Ming Tan

Dissertation: Regression Methods To Uncover Heterogeneous Effects With Applications To Analyzing Education Disparity 

Last Known Position: Senior Statistician, Abbvie

Charlotte Mann

Advisor: Johann Gagnon-Bartsch

Dissertation: Topics in Causal Inference Addressing Practical Data Challenges 

Last Known Position: Assistant Professor, California Polytechnic State University - San Luis Obispo

Jing Ouyang

Advisor: Gongjun Xu

Dissertation: Interpretable Latent Variable Models: Identifiability, Estimation, and Inference

Last Known Position: Assistant Professor, The University of Hong Kong 

Saptarshi Roy

Advisor: Ambuj Tewari

Dissertation: Statistics in the Modern Era: High Dimensions, Decision-Making, and Privacy

Last Known Position: Postdoctoral Fellow, University of Texas - Austin 

Hu Sun

Advisor: Yang Chen

Dissertation: Statistical Methods for Spatio-Temporal Tensor Data

Last Known Position: Quantitative Researcher, IMC Trading

Songkai Xue

Advisor: Yuekai Sun

Dissertation: Advances in Machine Learning Safety

Last Known Position: Research Scientist, Huawei

Enes Dilber

Advisor: Jonathan Terhorst

Dissertation: Advances in Statistical Methods for Evolutionary Analysis: From Natural Selection to Demographic Inference and Phylogenetics 

Last Known Position: Data Scientist, Google

Bach Viet Do

Advisors: Yang Chen & Long Nguyen

Dissertation: Mixture Modeling: Solar Application and Misspecification Behaviors 

Last Known Position: Machine Learning Research Scientist, Meta

Derek Hansen

Advisors: Ed Ionides & Jeff Regier

Dissertation: Mechanistic and Data-Adaptive Bayesian Methods for Scientific Inference 

Last Known Position: Senior Data Engineer, Northwell Health    

Daniel Iong

Advisor: Yang Chen

Dissertation: Inference Algorithms for Probabilistic Models With Applications in Epidemiology and Space Weather Forecasting 

Last Known Position: Senior Member of Technical Staff, The Aerospace Corporation

Rafail Kartsioukas

Advisor: Stilian Stoev

Dissertation: Topics on Anomaly Detection, High Dimensional Testing and Spectral Inference for Functional Data 

Last Known Position: Biostatistician, Medpace

Dan Kessler

Advisor: Liza Levina

Dissertation: Learning Structure in High-Dimensional Data with Applications to Neuroimaging 

Last Known Position: Assistant Professor of Statistics, University of North Carolina

Peter MacDonald

Advisors: Liza Levina & Ji Zhu

Dissertation: Structured Latent Space Models for Multiplex Networks 

Last Known Position: Assistant Professor, University of Waterloo

Robert Neale Trangucci

Advisor: Yang Chen

Dissertation: Bayesian Model Expansion for Selection Bias in Epidemiology  

Last Known Position: Assistant Professor of Statistics, Oregon State University 

Ziping Xu

Advisor: Ambuj Tewari

Dissertation: On the Benefits of Multitask Learning: A Perspective Based on Task Diversity  

Last Known Position: Assistant Professor, University of North Carolina  

Hamid Eftekhari

Advisors: Ya'acov Ritov & Moulinath Banerjee

Dissertation: Inference and Design in High-Dimensional Statistical Models

Last Known Position: Research 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 Strategist, Virtu Financial

Byoungwook Jang

Advisor: Alfred Hero

Dissertation: Probabilistic Decomposition in Machine Learning Problems

Last Known Position: Research Scientist, Anthropic

Yifan Jin

Advisor: Jonathan Terhorst

Dissertation: On Some Approximate Inference Approaches in Population Genetics 

Last Known Position: Founding Team, Complexity AI

Caleb Ki

Advisor: Jonathan Terhorst

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: Postdoctoral Fellow, ETH Zürich

Rayleigh Lei

Advisor: Long Nguyen

Dissertation: Modeling Simplex-valued Data and Latent Structures

Last Known Position: Statistics Research Specialist, Michigan State University

Chengcheng Li

Advisor: Gongjun Xu

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

Last Known Position: Senior Applied 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: Senior Machine Learning Engineer, Robinhood

Timothy Lycurgus

Advisor: Ben Hansen

Dissertation: Dry Runs and "PWRD" Aggregation: Two New Methods for Extracting Power from Careful Observation of a Randomized Controlled Trial's Context 

Last Known Position: Senior Data Scientist, Fidelity Investments

Chenchen Ma

Advisor: Gongjun Xu

Dissertation: Statistical Learning for Latent Attribute Models

Last Known Position: Research Scientist, Meta

Debarghya Mukherjee

Advisor: Ya'acov Ritov and Moulinath Banerjee

Dissertation: Analysis of High Dimensional Statistical Models with Discontinuity 

Last Known Position: Assistant Professor, Boston University

Laura Niss

Advisor: Ambuj Tewari and Yuekai Sun

Dissertation: Topics in Sequential Decision Making and Algorithmic Fairness

Last Known Position: Technical Staff, MIT Lincoln Labs

Nora Payne

Advisor: Johann Gagnon-Bartsch

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

Last Known Position: Statistician, Center for Disease Control

Zoe Rehnberg

Advisor: Johann Gagnon-Bartsch

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

Last Known Position: Assistant Professor - Statistics, California Polytechnic State Univiersity

Qianhua Shan

Advisor: Liza Levina

Dissertation: Network Inference with Applications in Neuroimaging

Last Known Position: Research Data Scientist, Meta

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

Advisors: Alfred Hero & Yang Chen

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

Last Known Position: Data Scientist, Google

Andrew Yarger

Advisors: Tailen Hsing & Stilian Stoev

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

Last Known Position: Assistant Professor, Purdue University

Kidus Asfaw

Advisor: Ed Ionides

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

Last Known Position: Data Scientist, Microsoft

Yinqiu He

Advisor: Gongjun Xu and Xuming He

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

Last Known Position: Assistant Professor of Statistics, University of Wisconsin - Madison

Baekjin Kim 

Advisor: Ambuj Tewari

Dissertation: Stability in Online Learning: From Random Perturbations in Bandit Problems to Differential Privacy 

Last Known Position: Machine Learning Engineer, Snap Inc

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: Assistant Professor of Biostatistics, University of Pennsylvania

Edward Wu

Advisor: Johann Gagnon-Bartsch

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

Last Known Position: Senior Producer - Data, Polling, and Election Analytics, CNN 

Anwesha Bhattacharyya
Advisor: Yves Atchade
Dissertation: Large-Scale Quasi-Bayesian Inference with Spike-and-Slab Priors
Last Known Position: Lead 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: Data Scientist, Google

Roger Fan
Advisor: Yuekai Sun and Shuheng Zhou 
Dissertation: Covariance Estimation with Missing and Dependent Data
Last Known Position: Research Scientist II, Amazon

Robyn Ferg
Advisor: Johann Gagnon-Bartsch
Dissertation: Modern Survey Estimation with Social Media and Auxiliary Data
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: Senior Research Scientist, Upstart

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

Yuqi Gu
Advisor: Gongjun Xu
Dissertation: Statistical Analysis of Structured Latent Attribute Models
Last Known Position: Assistant Professor of Statistics, Columbia University

Aritra Guha
Advisor: Long Nguyen
Dissertation: Inference and Interpretability in Latent Variable Modeling
Last Known Position: Lead Inventive Scientist, AT&T Labs, Inc.

Young Hun Jung
Advisor: Ambuj Tewari
Dissertation: New Directions in Online Learning: Boosting, Partial Information, and Non-Stationarity 
Last Known Position: Senior Applied Scientist, Moloco

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

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: Senior Data Scientist - Research, 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 and Bipartite Networks
Last Known Position: Data Scientist, Google

Xuefei Zhang
Advisor: Ji Zhu
Dissertation: Statistical Analysis for Network Data using Matrix Variate Models and Latent Space Models 
Last Known Position: Data Scientist, Google