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Alumni

Dissertations are held in the collections of
Stanford University Libraries.

Cohort: 2018-2019
Cohort Student Advisor Name Committee Names Dissertation
2018-2019 Rakesh Achanta Hastie Taylor, Tibshirani Boosting Like Path Algorithms for L1 Regularized Infinite Dimensional Convex Neural Networks
2018-2019 Yu Bai Duchi Montanari, Candes Optimization and statistical guarantees in modern learning problems
2018-2019 Nan Bi Taylor Tibshirani, Lai Topics in Selective Inference and its Application to Instrumental Variables
2018-2019 Alex Chin Ugander (MSE) Walther, Palacios Modern Statistical Approaches for Randomized Experiments Under Interference
2018-2019 Wenfei Du Tibshirani Taylor, Imbens (GSB) Some hierarchical and group regularization methods and applications
2018-2019 Leying Guan Tibshirani/Wong Efron Classification and testing under robust model assumptions
2018-2019 Eugene Katsevich Sabatti Candes, Montanari Multiple Testing with Structure and Exploration
2018-2019 Keli Liu Tibshirani Owen, Wager (GSB) A Computationally Conscious Search for Interactions
2018-2019 Jelena Markovic Taylor Tibshirani, Romano Statistical methods for adaptive data analysis
2018-2019 Paulo Orenstein Diaconis Chatterjee, Wong Topics in Robust Mean Estimation
2018-2019 Feng Ruan Duchi Johnstone, Candes Adapting local minimax theory to modern applications
2018-2019 Pragya Sur Candes Montanari, Johnstone A Modern Maximum Likelihood Theory for High-Dimensional Logistic Regression
2018-2019 Jeha Yang Johnstone Owen, Donoho Edgeworth approximations for spiked PCA models and applications
Cohort: 2017-2018
Cohort Student Advisor Name Committee Names Dissertation
2017-2018 Joseph Arthur Wong Owen, Tang Detection and validation of genomic structural variation from DNA sequencing data
2017-2018 Cyrus DiCiccio Romano Taylor, Tibshirani Hypothesis Testing Using Multiple Data Splitting
2017-2018 Zhou Fan Montanari/Johnstone Candes Eigenvalues in multivariate random effects models
2017-2018 Kelvin Guu Liang (CS) Wong, Mackey, Manning (CS) Learning to generate text, programs (and beyond) from weak supervision
2017-2018 Ya Le Hastie Efron, Taylor Topics in statistical learning with a focus on large-scale data
2017-2018 Snigdha Panigrahi Taylor Tibshirani, Sabatti An approximation-based framework for post-selective inference
2017-2018 Kris Sankaran Holmes Switzer, Efron Discovery and Visualization of Latent Structure with Applications to the Microbiome

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