David Donoho
Anne T. and Robert M. Bass Professor in the School of Humanities and Sciences
Statistics
Bio
David Donoho is a mathematician who has made fundamental contributions to theoretical and computational statistics, as well as to signal processing and harmonic analysis. His algorithms have contributed significantly to our understanding of the maximum entropy principle, of the structure of robust procedures, and of sparse data description.
Research Statement:
My theoretical research interests have focused on the mathematics of statistical inference and on theoretical questions arising in applying harmonic analysis to various applied problems. My applied research interests have ranged from data visualization to various problems in scientific signal processing, image processing, and inverse problems.
201617 Courses
 Introduction to Time Series Analysis
STATS 207 (Spr)  Introduction to the Bootstrap
STATS 208 (Spr)  Theory of Probability
STATS 116 (Aut) 
Independent Studies (8)
 Advanced Reading and Research
SCCM 499 (Win, Sum)  Independent Study
STATS 199 (Aut, Win, Spr, Sum)  Independent Study
STATS 299 (Aut, Win, Spr, Sum)  Industrial Research for Statisticians
STATS 298 (Aut, Win, Spr, Sum)  Industrial Research for Statisticians
STATS 398 (Aut, Win, Spr, Sum)  Master's Research
CME 291 (Win, Spr, Sum)  Ph.D. Research
CME 400 (Aut, Win, Spr, Sum)  Research
STATS 399 (Aut, Win, Spr, Sum)
 Advanced Reading and Research

Prior Year Courses
201516 Courses
 Multivariate Analysis and Random Matrices in Statistics
STATS 325 (Spr)
201415 Courses
 An Introduction to Compressed Sensing
CME 362, STATS 330 (Aut)  Introduction to Time Series Analysis
STATS 207 (Spr)  Introduction to the Bootstrap
STATS 208 (Spr)  Modern Spectral Analysis
STATS 333 (Spr)
201314 Courses
 An Introduction to Compressed Sensing
CME 362, STATS 330 (Aut)  Introduction to Time Series Analysis
STATS 207 (Spr)  Introduction to the Bootstrap
STATS 208 (Spr)
 Multivariate Analysis and Random Matrices in Statistics