STUDENTS  

 Past Ph.D Students
 Past Post-Doctoral Students
 Present Ph.D Students
 

Present Ph.D Students

Zijun Gao
Swarnadip Ghosh (co-advised by Art Owen)
Elena Tuzhilina


 

Past Ph.D Students

21. Junyang Qian, 2020
Large-Scale Statistical Learning Methods and Algorithms
PDT Partners, New York.

20. Rakesh Achanta, 2019
Boosting like Path Algorithms For L1 Regularized Infinite Dimensional Convex Neural Networks
Volunteer, Sadhguru's Isha Foundation

19. Ya Le, 2018
Topics in Statistical Learning with a Focus on Large-Scale Data
Data Science team, Google Brain

18. Charles Zheng, 2017
Supervised Learning of Representations
(co-advided with Jonathan Taylor, and mentored by Yuval Benjiamini)
Researcher in Section on Functional Imaging Methods, Laboratory of Brain and Cognition, National Institute of Mental Health.

17. Hristo Spassimirov Paskov, 2016
Learning with N-grams: from Massive Scales to Compressed Representations.
(co-advised with John Mitchell, CS).
Arthur Samuel Award for best dissertation in Computer Science at Stanford.
Research group at Apple

16. Qingyuan Zhao, 2016
Topics in Causal and High Dimensional Inference
University Lecturer in Statistics, University of Cambridge www.statslab.cam.ac.uk/~qz280/

15. Will Fithian, 2015
Topics in Adaptive Inference
Assistant Professor, University of California, Berkeley.

14. Jason Lee, 2015
Selective Inference and Learning Mixed Graphical Models
(co-advised with Jonathan Taylor)
Assistant professor of Electrical and Computer Engineering and Computer Science (secondary), Princeton University

13. Michael Lim, 2013
The Group Lasso: Two Novel Applications.
Quantitative finance, The Voleon Group, San Francisco (2017 - )

12. Rahul Mazumder, 2012
Topics in Sparse Multivariate Statistics.
Associate Professor, Operations Research and Statistics group at MIT Sloan School of Management
http://www.mit.edu/~rahulmaz/

11. Donal McMahon, 2009
Research Synthesis for Multiway Tables of Varying Shapes and Size
Group Manager of Data Platforms and Head of Data Science at Indeed.com., Austin, Texas

10. Ping Li, 2007
Stable Random Projections and Conditional Random Sampling, Two Sampling Techniques for Modern Massive Datasets
Head of Cognitive Computing Lab (CCL) at Baidu
Associate Professor, Departments of Statistics and Computer Science, Rutgers University
http://www.stanford.edu/~pingli98

9. Gill Ward, 2007
Statistics in Ecological Modeling: Presence-Only Data and Boosted Mars
Google (Youtube), Mountain View.
http://www.stanford.edu/~gward

8. Mee-Young Park, 2006
Generalized Linear Models with Regularization
Quantitative Analyst, Google, Mountain View
http://mypark.jot.com/WikiHome

7. Hui Zou, 2005
Some Perspectives of Sparse Statistical Modeling
Professor, Department of Statistics, University of Minnesota
http://www.stat.umn.edu/~hzou

6. Saharon Rosset, 2003
Topics in Regularization and Boosting
(co-advised with Jerome Friedman)
Professor, School of Mathematical Sciences, Tel Aviv University
http://www.tau.ac.il/~saharon

5. Ji Zhu, 2003
Flexible Statistical Modelling
Professor, Department of Statistics, University of Michigan
http://www.stat.lsa.umich.edu/~jizhu/

4. Mu Zhu, 2001
Feature Extraction and Dimension Reduction with Applications to Classification and the Analysis of Co-occurrence Data
Professor, Statistics Department, University of Waterloo, Canada
http://www.stats.uwaterloo.ca/~m3zhu

3. Gareth James, 1998
Majority Vote Classifiers: Theory and Applications
Vice Dean for Faculty and Academic Affairs, E. Morgan Stanley Chair in Business Administration, Professor of Data Sciences and Operations, Marshall School of Business, USC
http://www-rcf.usc.edu/~gareth

2. Dan Rubinstein, 1997
Discriminative versus Informative Learning
CEO and co-founder of Reflectivity (acquired by Texas Instruments)
CEO at Physera, Inc., Palo Alto | Product Management at Google | Facebook | Palantir

1. Neil Crellin, 1996
Modeling Image Sequences, with Particular Applications to FMRI Data
Site Reliability Manager, Google, Mountain View

 

Past Post-Doctoral Students

Lukasz Kidzinski, 2016-2019 (Mobilize Center)
Ph.D Universite Libre de Bruxelles
AI Researcher at Saliency.ai. See kidzinski.com

Julia Viladomat, 2011-2013
Ph.D Universidad Carlos III de Madrid
Data Scientist Adobe Labs

Dirk Ormoneit, 2000-2001
Director of Research, Bluecrest Capitol Management, London
http://robotics.stanford.edu/~ormoneit

Eva Cantoni, 1999-2000
Associate Professor, Faculty of Economics and Social Science, University of Geneva.
http://www.unige.ch/ses/dsec/staff/faculty/Cantoni-Eva.html




 © copyright 2003 Trevor Hastie - All rights reserved.