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
- Promit Ghosal Probability, Mathematical Physics, Statistics
- Jimmy He Probability, Algebraic Combinatorics
- Han Huang High dimensional Probability, Random Matrices, Random Graphs
- Pakawut Jiradilok Algebraic Combinatorics, Asymptotic Combinatorics, Combinatorial Inequalities, Probability, Statistics
- Anya Katsevich Stochastic analysis, interacting particle systems, statistics
- Peter Kempthorne Statistics, Financial Mathematics
- Dan Mikulincer Probability, High-Dimensional Geometry, Functional Inequalities
- Yair Shenfeld Probability, Convex Geometry
- Youngtak Sohn Probability, Statistics, Machine Learning
- Ilias Zadik Mathematics Of Machine Learning, Information Theory, Statistics, Probability Theory
Researchers & Visitors
- Michael Simkin Probabilistic combinatorics, random graphs, and random processes
Graduate Students*
- Shrey Aryan Optimal Transport, PDEs and Harmonic Analysis
- Sinho Chewi optimal transport, optimization, sampling, statistics
- Byron Chin
- Max Daniels High-dimensional statistics, optimization, sampling algorithms, machine learning
- Patrik Gerber
- Sergei Korotkikh algebraic combinatorics, integrable probability
- Nitya Mani
- Ron Nissim Mathematical Physics, Integrable Systems, Stochastic Processes
- George Stepaniants Statistical Learning of Differential Equations, Optimal Transport in Biology
- Roger Van Peski Integrable probability, algebraic combinatorics, random matrix theory
- Pu Yu
*Only a partial list of graduate students