Probability & Statistics
Following the work of Kolmogorov and Wiener, probability theory after WW II concentrated on its connections with PDEs and harmonic analysis with great success. It deserves credit for some of the most delicate results in modern harmonic analysis; it provides the foundation on which signal processing and filtering theory are built in engineering; and it played a critical role in the mathematical attempts to rationalize quantum field theory. Combinatorial branches of probability theory were overshadowed during that period but are now returning to the fore. Probability theory lies at the crossroads of many fields within pure and applied mathematics, as well as areas outside the boundaries of the mathematics department. Statistics is a mathematical field with many important scientific and engineering applications.
Department Members in This Field
Faculty
- Alexei Borodin Integrable Probability
- Elchanan Mossel Probability, Algorithms and Inference
- Philippe Rigollet Statistics, Machine Learning
- Scott Sheffield Probability and Mathematical Physics
- Nike Sun Probability, statistical physics
Instructors & Postdocs
- Tomas Berggren Integrable Probability
- Sky Cao Probability theory, Yang-Mills
- Ziang Chen applied analysis, applied probability, statistics, optimization, machine learning
- Jason Gaitonde Algorithms, Learning Theory, Probability Theory, Networks
- Jimmy He Probability, Algebraic Combinatorics
- Pakawut Jiradilok Algebraic Combinatorics, Asymptotic Combinatorics, Combinatorial Inequalities, Probability, Statistics
- Anya Katsevich High dimensional statistics, Bayesian inference
- Konstantinos Kavvadias Probability and Mathematical Physics
- Peter Kempthorne Statistics, Financial Mathematics
- Dan Mikulincer Probability, High-Dimensional Geometry, Functional Inequalities
- Michael Simkin Probabilistic combinatorics, random graphs, and random processes
- Youngtak Sohn Probability, Statistics, Machine Learning
- Anirudh Sridhar Statistical inference, network cascades, graph algorithms, graph matching
Graduate Students*
- Shrey Aryan Optimal Transport, PDEs and Harmonic Analysis
- Adam Block Learning Theory, Statistics
- Anna Brandenberger
- Andrey Bryutkin Mathematics of Data, Statistics, Physical Applied Mathematics
- Byron Chin
- Max Daniels High-dimensional statistics, optimization, sampling algorithms, machine learning
- Hang Du Probability, interactions with statistical physics, combinatorics and TCS
- Patrik Gerber
- Seokmin Ha
- Frederic Jorgensen
- Nitya Mani
- Matthew Nicoletti Probability, Mathematical Physics
- Ron Nissim Mathematical Physics, Probability, PDEs
- George Stepaniants Statistical Learning of Differential Equations, Optimal Transport in Biology
- Pu Yu
*Only a partial list of graduate students