Ph.D. Dissertations Supervised:

1. Bertrand S. Clarke (1989). Asymptotic Cumulative Risk and Bayes Risk under Entropy Loss, with Applications. University of Illinois at Urbana-Champaign. [Was Assistant Professor at Purdue University; then Professor at University of British Columbia and University of Miami; Now Chairman, Department of Statistics, University of Nebraska]


2. Chyong-Hwa Sheu (1989). Density Estimation with Kullback-Leibler Loss. University of Illinois at Urbana-Champaign.


3. Yuhong Yang (1996). Minimax Optimal Density Estimation. Yale University. [Was Assistant Professor at Iowa State University; Now Professor at University of Minnesota, Department of Statistics.]


4. Qun (Trent) Xie (1997). Minimax Coding and Prediction. Yale University. [Was at GE Capital, Inc., Fairfield, CT. Now a Professor at Tsinghua Univ.]


5. Gerald Cheang (1998). Neural Net Approximation and Estimation of Functions. Yale University. [Now a Professor at Singapore Technical and Education University.]


6. Jason Cross (1999). Universal Portfolios for Target Classes having a Continuous Form of Dependence on Side Information. Yale University. [Was at an investment start-up firm with Myron Scholes in New York. Now runs an investment firm in Minneapolis, Minnesota.]


7. Qiang (Jonathan) Li (1999). Estimation of Mixture Models. Yale University. [Was at KPMG Financial Services, New York. Then at Stanford Research Institute, Palo Alto. Now at Radar Networks, Inc., San Franscisco]


8. Feng Liang (2002). Exact Minimax Predictive Density Estimation. Yale University. [Was Assistant Professor Department of Statistics, Duke University. Now Associate Professor, Department of Statistics, University of Illinois at Urbana-Champaign]


9. Gilbert Leung (2004). Information Theory and Mixing Least Squares Regression. Yale University. [At Qualcomm, first in San Diego, now near San Jose.]


10. Wei Qiu (2007). Maximum Wealth Portfolios. Yale University. [J.P. Morgan Chase, Columbus, Ohio.]


11. Cong Huang (2008). Risk of Penalized Least Squares, Greedy Selection and L1-Penalization for Flexible Function Libraries. Yale University. [Was at Columbia University, Department of Statistics. Now in China.]


12. Xi Luo (Rossi) (2009). Penalized Likelihoods: Fast Algorithms and Risk Bounds. Yale University. [Was at University of Pennsylvania, postdoc with Tony Cai, Department of Statistics. Now Assistant Professor at Brown University, Department of Biostatistics.]


13. Antony Joseph (2012). Achieving Information Theoretic Limits with High Dimensional Regression. Yale University. Co-developer at Yale of capacity-achieving sparse superposition codes. [Was at University of California, Berkeley, postdoc with Bin Yu, Department of Statistics. Now at Walmart Research.]


14. Sanghee Cho (2014). High-Dimensional Regression with Random Design, including Sparse Superposition Codes. Yale University. [At GE Research, Schenectady, New York]


15. Sabyasachi Chatterjee (2014). Adaptation in Estimation and Annealing. Yale University. [Was Postdoc with John Lafferty, Department of Statistics, University of Chicago. Now Assistant Professor, Department of Statistics, University of Illinois at Urbana-Champaign.]


16. Xiao (Grace) Yang (2015). Compression and Predictive Distributions for Large Alphabets. Yale University. [Now at Apple Inc., Cupertino, California.]


17. Cynthia Rush (May 2016). Iterative Algorithms for Inference and Optimization, with Applications in Communications and Compressed Sensing. Yale University. [Now Assistant Professor at Department of Statistics, Columbia University.]


18. W. David Brinda (May 2018). Adaptive Estimation with Gaussian Radial Basis Mixtures. Yale University. [Now Lecturer at Department of Statistics and Data Science, Yale University.]


19. Jason A. Klusowski (May 2018). Density, Function, and Parameter Estimation with High-Dimensional Data. Yale University. [Now Assistant Professor at Department of Statistics, Rutgers University.]