Alumni
Visit Stanford University Libraries to search for the PhD dissertations of our graduates.
Graduation Year
Student
Dissertation
Advisor
Committee Members
Phase Transitions of Disordered Systems and High Dimensional Inference
Dembo
Chatterjee, Montanari
Applied Statistical Methods for High-Dimensional Generalized Linear Models
Candes
Montanari, Taylor
Topics in Exact Asymptotics for High-dimensional Regression
Montanari
Candes, Donoho
Advances in Contextual Multi-armed Bandits, Dynamic Treatment Strategies, and Type 1 Error Rate Guarantees in Confirmatory Adaptive Multi-arm Clinical Trials
Lai
Lavori (BDS), Lu (BDS), Palacios
Extending the Reach of the Lasso and Elastic Net Penalties: Methodology and Practice
Tibshirani
Art Owen, Guenther Walther
Statistics and Uncertainty Quantification in Graphs and Networks with Biomedical Applications
Holmes
Friedman, Leskovec (CS)
Topics in Machine Learning for Causal Inference with Applications in Social Science
Athey (Econ)
Owen, Hastie
The Algebra and Machine Representation of Statistical Models
Candes
Hastie, Chambers, Musen (Med/BDS)
Large-scale and High-dimensional Statistical Learning: Methods and Algorithms
Hastie
Tibshirani, Rivas (BDS)
New Methods for Variable Importance Testing with Applications to Genetic Studies
Candes
Sabatti, Tibshirani
Asymptotic Theory for Large Random Matrices and its Applications
Dembo
Chatterjee, Montanari
Boosting Like Path Algorithms for L1 Regularized Infinite Dimensional Convex Neural Networks
Hastie
Taylor, Tibshirani
Topics in Selective Inference and its Application to Instrumental Variables
Taylor
Tibshirani, Lai
Modern Statistical Approaches for Randomized Experiments Under Interference
Ugander (MSE)
Walther, Palacios
Some hierarchical and group regularization methods and applications
Tibshirani
Taylor, Imbens (GSB)
Health and loan default risk analytics: Prediction models and their evaluation
Lai
Walther, Lu (BDS)
A Modern Maximum Likelihood Theory for High-Dimensional Logistic Regression
Candes
Montanari, Johnstone
Detection and validation of genomic structural variation from DNA sequencing data
Wong
Owen, Tang
Learning to generate text, programs (and beyond) from weak supervision
Liang (CS)
Wong, Mackey, Manning (CS)
An approximation-based framework for post-selective inference
Taylor
Tibshirani, Sabatti
Discovery and Visualization of Latent Structure with Applications to the Microbiome
Holmes
Switzer, Efron
Scalable Estimation and Inference for Massive Linear Mixed Models with Crossed Random Effects
Owen
Tibshirani, Mackey
Two Parameter Inference Methods in Likelihood-free Models: Approximate Bayesian Computation and Contrastive Divergence
Wong
Lai, Diaconis