PhD Alumni

Graduated Between:

Start date

Year

End date

Year

2020

Zsolt Bartha Advisor: Nike Sun Dissertation: Replica Symmetry Breaking in the Random Regular k-NAE-SAT Problem	Stephanie DeGraaf Advisor: Elizabeth Purdom Dissertation: Time-Course Analysis and Clustering of Gene Expression Data	Billy Fang Advisor: Adityanand Guntuboyina and Martin J. Wainwright Dissertation: Shape-constrained regression in misspecified and multivariate settings
Chun Yu Hong (Johnny) Advisor: Will Fithian and Perry de Valpine Dissertation: Latent Variable Models: Maximum Likelihood Estimation and Microbiome Data Analysis	Sara Stoudt Advisor: Will Fithian and Perry de Valpine Dissertation: A Statistical Investigation of Species Distribution Models and Communication of Statistics Across Disciplines

2019

Jianbo Chen Advisor: Martin Wainwright and Michael Jordan Dissertation: Towards Interpretability and Robustness of Machine Learning Models	Yuansi Chen Advisor: Bin Yu Dissertation: Fast MCMC algorithms, Stability and DeepTune	Ryan Giordano Advisor: Michael Jordan and Jon McAuliffe Dissertation: On the Local Sensitivity of M-Estimation: Bayesian and Frequentist Applications
Geno Guerra Advisor: Rasmus Nielsen Dissertation: Statistical Inference under the Multispecies Coalescent: Methods and Theory	Steve Howard Advisor: Jasjeet Sekhon and Jon McAuliffe Dissertation: Sequential and Adaptive Inference Based on Martingale Concentration	Yan Huang Advisor: Haiyan Huang Dissertation: Overcoming the Common Challenges in Differential Gene Expression Analysis Studies
Karl Kumbier Advisor: Bin Yu Dissertation: Domain-inspired machine learning for hypothesis extraction in biological data	Lihua Lei Advisor: Peter J. Bickel and Michael I. Jordan Dissertation: Modern Statistical Inference for Classical Statistical Problems	Jamie Murdoch Advisor: Bin Yu Dissertation: Interpretable deep learning for natural language processing
Kellie Ottoboni Advisor: Philip Stark Dissertation: Classical Nonparametric Hypothesis Tests with Applications in Social Good	Sourav Sarkar Advisor: Alan Hammond Dissertation: Last Passage Percolation and the Slow Bond Problem	Omid Shams Solari Advisor: Peter Bickel and Ben Brown Dissertation: Large-Scale Interpretable Multi-View Learning for Very High-Dimensional Problems with Application to Multi-Omic Data
Simon Walter Advisor: Jasjeet Sekhon and Bin Yu Dissertation: High-dimensional and causal inference	Jason Wu Advisor: Peng Ding Dissertation: Randomization Tests under the Potential Outcomes Framework

2018

Nicholas Boyd Advisor: Michael Jordan and Ben Recht Dissertation: Sets as Measures: Optimization and Machine Learning	Jonathan Fischer Advisor: Yun S. Song Dissertation: Statistical Methods and Analyses in Computational Genomics: Explorations of Eukaryotic Transcription	Dave Graham-Squire Advisor: Deborah Nolan Dissertation: Behavioral Types: A New Perspective on Estimating Treatment Eﬀects in Social Science Experiments with Binary Responses
Soumendu Sundar Mukherjee Advisor: Peter Bickel Dissertation: On Some Inference Problems for Networks	Sujayam Saha Advisor: Bin Yu & Aditya Guntuboyina Dissertation: Information Theory, Dimension Reduction and Density Estimation	Funan Shi Advisor: Haiyan Huang Dissertation: High Dimensional Statistical and Computational Methods for Knowledge Discovery and Data Mining in Biomedical Data
Bradly Stadie Advisor: Pieter Abeel and Peter Bartlett Dissertation: Learning as a Sampling Problem	Yuting Wei Advisor: Martin Wainwright & Adityanand Guntuboyina Dissertation: A geometric perspective on some topics in statistical learning	Ashia Wilson Advisor: Michael I. Jordan and Ben Recht Dissertation: Lyapunov Arguments in Optimization

2017

Hye Soo Choi Advisor: Steve N. Evans Dissertation: The Doob-Martin compactification of Markov chains of growing words	Christine Kuang Advisor: Bin Yu & Jasjeet Sekhon Dissertation: Predictive and Interpretable Text Machine Learning Models with Applications in Political Science	Lisha Xiang Li Advisor: David Aldous Dissertation: Inference on Graphs: From Probability Methods to Deep Neural Networks
Wenpin Tang Advisor: Jim Pitman Dissertation: Continuous paths in Brownian motion and related problems	Jonathan Terhorst Advisor: Yun S. Song Dissertation: Demographic Inference from Large Samples: Theory and Methods	Yumeng Zhang Advisor: Allan Sly Dissertation: Phase Transitions of Random Constraints Satisfaction Problem

2016

Adam Bloniarz Advisor: Bin Yu Dissertation: Leveraging latent structure in high-dimensional data: causality, neuroscience, and nonparametrics	Jonathan Hermon Advisor: Allan Sly Dissertation: Maximal Inequalities and Mixing Times	Christine Ho Advisor: Haiyan Huang, Elizabeth Purdom Dissertation: Statistical Modeling and Analysis for Biomedical Applications
Jeffrey Regier Advisor: Jon McAuliffe Dissertation: Topics in large-scale statistical inference	Geoffrey Schiebinger Advisor: Benjamin Recht Dissertation: Sparse Inverse Problems: The Mathematics of Precision Measurement	Linda N. Tran Advisor: Cari Kaufman and Deborah Nolan Dissertation: Forecasting high-dimensional state-spaces in the presence of model error
Siqi Wu Advisor: Bin Yu Dissertation: Dictionary learning: analysis of spatial gene expression data and local identifiability theory

2015

Riddhipratim Basu Advisor: Allan Sly Dissertation: Lipschitz Embeddings of Random Objects and Related Topics	John Kamm Advisor: Yun Song Dissertation: One and Two Locus Likelihoods Under Complex Demography	Hongwei Li Advisor: Bin Yu Dissertation: Theoretical Analysis and Efficient Algorithms for Crowdsourcing
Miles Lopes Advisor: Peter J. Bickel Dissertation: Some Inference Problems in High-Dimensional Linear Models	Miklos Z. Racz Advisor: Elchanan Mossel Dissertation: Influences in Voting and Growing Networks	Y.X. Rachel Wang Advisor: Haiyan Huang, Peter Bickel Dissertation: Problems in Network Modeling: Estimating Edges and Community Detection