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Alumni

Visit Stanford University Libraries to search for the PhD dissertations of our graduates.

Graduation Year
Student
Dissertation
Advisor
Committee Members

Topics in Selective and Causal Inference

Candes

Hastie, Sabatti

Towards Modern Datasets: Laying Mathematical Foundations to Streamline Machine Learning

Duchi/Montanari

Candes

Conditional Guarantees in Model-Free Inference

Candes

Duchi, Hastie

Mathematical Statistics in 2025

Donoho

Johnstone, Montanari

Detecting and Measuring Important Variables: Novel Methods with Statistical Guarantees

Sabatti

Candes, Hastie, Palacios

Scalable Statistical Models for Personalized Recommendation: Incorporating Random Slopes and Latent Structure

Hastie

Taylor, Owen

Topics in Causal Inference and Distribution Shifts

Fox

Rothenhaeusler, Johari (MS&E)

Topics in Multivariate Time Series Evaluation and Forecasting

Hong (Econ)

Lai, Romano, Fox, Taylor

Precise Randomized Experiments Through Design and Estimation

Owen

Rothenhaeusler, Wager

Experimental Design Methods for Treatment Effect Estimation Under Constraints

Owen

Rothenhaeusler, Baiocchi

Statistical Advances in Synthetic Data Generation and Longitudinal Analysis

Tian

Taylor, Efron

New Perspectives on Dimensionality Reduction and Selective Inference

Hastie

Taylor, Owen

Fast and Scalable Solvers for Penalized Regression with Sparsity

Hastie

Taylor, Rothenhaeusler

Coalescent Structures and Their Generalizations

Palacios

Rosenberg (Bio), Sabatti, Walther

Connecting Frequentist and Bayesian Inference

Efron

Tibshirani, Wong

Applications of Data Fission: Spatial Estimation and Model-free Selective Inference

Taylor

Switzer, Tibshirani

Expanded Coverage Guarantees for Conformal Inference

Candes

Duchi, Schramm

Topics on Finite-sample Valid Inference and the Finite Population Bootstrap

Candes/Walther

Taylor

Modern Statistical Methodology for Generalizable and Trustworthy Inference

Candes/Rothenhaeusler

Owen

Methods for Causal Inference with Limited or No Overlap

Ugander (MSE)

Owen, Rothenhaeusler

Topics in Data Fusion with Applications to Agriculture

Owen/Lobell (Earth System Science)

Switzer

Advances in Quasi-Monte Carlo

Owen

Palacios, Taylor

Super-polynomial Accuracy of Randomized Nets Using the Median-of-means

Owen

Chatterjee, Schramm

Eigenvalue-based Regressors in High Dimensions

Donoho

Johnstone, Owen

Computational and Informational Limits in High-dimensional Statistical Problems

Montanari

Candes, Dembo

Three Essays in Causal Inference

Rothenhaeusler

Owen, Romano

Estimation and Testing Methods for Causal Inference with Interference

Imbens (Econ) / Ugander (MSE)

Owen

Learning with Neural Networks in High Dimensions

Montanari

Donoho, Johnstone

On Some Topics in Statistical Learning: Cluster-Aware Lasso & Others

Tibshirani

Hastie, Palacios

Stability of Solutions of Random Optimization Problems Under Small Perturbations

Chatterjee

Dembo, Diaconis

Applications of Cooperative Game Theory to Interpretable Machine Learning

Owen

Palacios, Taylor

Permutation-Based Inference in Time Series Analysis

Romano

Duchi, Owen

Causal Inference with Non-standard Experimental Designs

Wager (GSB)

Hastie, Siegmund

Information-Theoretic and Computational Perspectives

Montanari

Johnstone, Schramm

Inference for Prediction Error Beyond the IID Assumption

Tibshirani

Hastie, Owen

Change-point Detection in Mean or Variance or Both

Siegmund

Lai, Linderman

Some applications of graph limits in probability and statistics

Chatterjee

Montanari, Dembo

Some probabilistic aspects of Yang-Mills

Chatterjee

Diaconis, Dembo

Confident and reliable statistical predictions in changing environments

Duchi

Candes, Liang (CS)

Applications of Machine Learning to Some Statistical Inference Problems

Hastie

Tibshirani, Wager

Scalable Inference for Crossed Random Effects Models

Owen/Hastie

Hastie, Linderman, Athey (GSB)

Reliability and stability in statistical and machine learning problems

Duchi

Candes, Donoho, Rothenhaeusler

Nonparametric perspectives on empirical Bayes

Wager (GSB)

Candes, Tibshirani

A Neural Network with Feature Sparsity

Tibshirani

Duchi, Hastie

Causal and Selective Inference in Complex Statistical Models

Candes/Wager (GSB)

Hastie

Likelihood ratio testing in critically-spiked Wigner models

Johnstone

Owen, Dembo

Topics in multiple hypothesis testing and robustification of estimators through causal inference methods

Zou (BDS)

Candes, Owen

Phase Transitions of Disordered Systems and High Dimensional Inference

Dembo

Chatterjee, Montanari

Advances in multivariate statistics and its applications

Hastie

Tibshirani, Segal (UCSF)

Applied Statistical Methods for High-Dimensional Generalized Linear Models

Candes

Montanari, Taylor