| name | thesis title | year PhD degree awarded |
|---|---|---|
| Deborah Nolan | U-processes | 1986 |
| Jean Kyung Kim | An asymptotic theory for optimization estimators with non-standard rates of convergence | 1988 |
| Robert Sherman | U-processes and semiparametric estimation | 1991 |
| Hemant Ishwaran | Rates of convergence in semiparametric mixture models | 1993 |
|
David Riceman (jointly supervised with John Hartigan) |
An estimator for the linear model | 1996 |
| Yuewu Xu | Asymptotic theory in the presence of unidentified parameters | 1997 |
| Andrew Carter | Asymptotic equivalence of nonparametric experiments | 2000 |
| Gheorghe Doros | A class of one-step estimators in interval censoring | 2004 |
| Peter Radchenko | Asymptotics under nonstandard conditions | 2004 |
|
Stephan Winkler (Applied Math; jointly supervised with Sekhar Tatikonda from Electrical Engineering) |
Uniqueness of Gibbs measures with application to Gibbs sampling and the sum-product algorithm | 2007 |
|
Steven Jaslar (Applied Math; jointly supervised with Sekhar Tatikonda) |
The asymptotics of combinatorial problems on random graphs | 2009 |
|
Wei Dou (jointly supervised with Harry Zhou) |
Functional regressions for general exponential families: a theoretical and applied study | 2010 |
|
Michael Kane (jointly supervised with Jay Emerson) |
Scalable strategies for computing with massive sets of data | 2010 |
| Adityanand Guntuboyina | Minimaxity and f-divergences | 2011 |
|
Kyoung Hee (Arlene) Kim (jointly supervised with Harry Zhou) |
Minimax bounds for estimation of normal location mixtures | 2012 |
|
Xiaoqian (Dana) Yang (jointly supervised with Yihong Wu and John Lafferty) |
A few topics in statistics | 2019 |
| Elena Khusainova | Essays in respondent driven sampling and interpretable machine learning | 2020 |