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Alumni

Dissertations are held in the collections of
Stanford University Libraries.

Cohort: 2020-2021
Cohort Student Advisor Name Committee Names Dissertation
2020-2021 Michael Celentano Montanari Candes, Donoho Topics in Exact Asymptotics for High-dimensional Regression
2020-2021 Nima Hamidi Bayati (GSB) Lai, Candes Minimax Regret Bounds for Stochastic Linear Bandit Algorithms
2020-2021 Zhimei Ren Candes Tibshirani, Owen Model-Free Methods for Multiple Testing and Predictive Inference
2020-2021 Michael Benjamin Sklar Lai Lavori (BDS), Lu (BDS), Palacios Advances in Contextual Multi-armed Bandits, Dynamic Treatment Strategies, and Type 1 Error Rate Guarantees in Confirmatory Adaptive Multi-arm Clinical Trials
2020-2021 Youngtak Sohn Dembo Chatterjee, Montanari Phase Transitions of Disordered Systems and High Dimensional Inference
2020-2021 Jingyi Kenneth Tay Tibshirani Art Owen, Guenther Walther Extending the Reach of the Lasso and Elastic Net Penalties: Methodology and Practice
Cohort: 2019-2020
Cohort Student Advisor Name Committee Names Dissertation
2019-2020 Mona Azadkia Chatterjee Taylor, Bayati (GSB) A Nonparametric Measure of Conditional Dependence
2019-2020 Stephen Bates Candes Tibshirani, Wager Causal Inference in Genetic Trio Studies
2019-2020 Claire Donnat Holmes Friedman, Leskovec (CS) Statistics and Uncertainty Quantification in Graphs and Networks with Biomedical Applications
2019-2020 Rina Friedberg Athey (Econ) Owen, Hastie Topics in Machine Learning for Causal Inference with Applications in Social Science
2019-2020 Jelena Markovic Taylor Tibshirani, Romano Statistical methods for adaptive data analysis
2019-2020 Evan Patterson Candes Hastie, Chambers, Musen (Med/BDS) The Algebra and Machine Representation of Statistical Models
2019-2020 Junyang Qian Hastie Tibshirani, Rivas (BDS) Large-scale and High-dimensional Statistical Learning: Methods and Algorithms
2019-2020 Evan Rosenman Owen/Baiocchi Palacios Making Causal Conclusions from Heterogeneous Data Sources
2019-2020 Matteo Sesia Candes Sabatti, Tibshirani New Methods for Variable Importance Testing with Applications to Genetic Studies
2019-2020 Andy Tsao Diaconis Chatterjee, Charikar (CS) Sampling Methods for Perfect Bipartite Matchings
2019-2020 Jun Yan Dembo Chatterjee, Montanari Asymptotic Theory for Large Random Matrices and its Applications
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 When do gradient methods work well in non-convex learning problems?
2018-2019 Nan Bi Taylor Tibshirani, Lai Topics in Selective Inference and its Application to Instrumental Variables

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