Algebra, Number Theory, and Algebraic Geometry
- Matt Baker — Number Theory, Arithmetic Geometry, Combinatorics
- Greg Blekherman — Applied and Real Algebraic Geometry
- Harold Blum — Algebraic Geometry
- Alex Dunn — Analytic Number Theory, L-functions, Automorphic Forms
- Ernie Croot
- Plamen Iliev
- Anton Leykin — Computational Algebraic Geometry
- Julia Lindberg - Applied and Computational Algebraic Geometry
- Josephine Yu
- Anton Zeitlin — Representation Theory with applications in Geometry, Topology, and Mathematical Physics
Analysis
- Greg Blekherman — Moments Problems
- Gong Chen
- Ernie Croot
- Mohammad Ghomi — Differential Geometry and Topology
- Christopher Heil — Harmonic Analysis
- Christian Houdré
- Plamen Iliev
- Michael Lacey — Fourier Analysis, Weighted Inequalities
- Wing Suet Li — Operator Theory
- Galyna Livshyts
- Michael Loss
- Doron Lubinsky — Harmonic Analysis, Approximation Theory
- John McCuan — Diff. Geometry and Partial Differential Eqns.
- Shahaf Nitzan
- Tobias Ried — Optimal Transport, Regularity Theory, Nonlinear PDEs, Quantum Mechanics, Disordered Systems
- Andrzej Swiech
Applied and Computational Math
- Leonid Bunimovich
- Hannah Choi - Computational Neuroscience, Neural Networks, Neural Coding
- Luca Dieci — Numerical Methods, Dynamical Systems, Matrix Computation
- Guillermo Goldsztein — Applied Mathematics
- Sung Ha Kang — Image Processing, Numerical Analysis
- Rachel Kuske
- Anton Leykin — Computational Algebraic Geometry
- Julia Lindberg - Polynomial and Nonlinear Optimization, Polynomial System Solving
- Wing Suet Li — Signal Processing
- Wenjing Liao — High Dimensional Data Analysis, Manifold Learning, Signal Processing
- Yingjie Liu — Numerical Methods for PDE
- Martin Short
- Molei Tao — Deep Learning, Optimization, Sampling, Measure Transport, Generative Modeling, AI4Science
- Haomin Zhou
- Wei Zhu — (Scientific) Machine Learning, Statistical Learning Theory, Generative Models, and Optimization
Differential Equations
- Leonardo Abbrescia — Hyperbolic PDEs, Fluid Mechanics, Singularity formation, General Relativity
- Gong Chen
- Xu-Yan Chen
- Luca Dieci — Numerical Methods, Dynamical Systems, Matrix Computation
- Albert Fathi — Hamilton-Jacobi Equation
- Zhiwu Lin — Fluid Dynamics, Plasma Physics, Stability Theory
- Ronghua Pan — Nonlinear PDEs, Fluid Dynamics, General Relativity
- Andrzej Swiech
- Tobias Ried — Optimal Transport, Regularity Theory, Nonlinear PDEs, Quantum Mechanics, Disordered Systems
- Molei Tao — Deep Learning, Optimization, Sampling, Measure Transport, Generative Modeling, AI4Science
- Mike Wolf — Teichmuller Theory (classical and higher rank), Geometric Variational Problems
- Chongchun Zeng
- Haomin Zhou
- Wei Zhu — (Scientific) Machine Learning, Statistical Learning Theory, Generative Models, and Optimization
Discrete Mathematics
- Matt Baker — Number Theory, Arithmetic Geometry, Combinatorics
- Greg Blekherman
- Ernie Croot
- Xiaoyu He — Extremal Combinatorics, Probabilistic Combinatorics, Ramsey Theory, Additive Combinatorics
- Christine Heitsch
- Christian Houdré
- Tom Kelly
- Anton Leykin — Computational Algebraic Geometry
- Galyna Livshyts
- Rose McCarty — Graph Theory, Algorithms and Complexity, Discrete Geometry
- Molei Tao — Deep Learning, Optimization, Sampling, Measure Transport, Generative Modeling, AI4Science
- Xingxing Yu
- Josephine Yu
Dynamical Systems
- Alex Blumenthal — Smooth Ergodic Theory, Random Dynamics, Infinite Dimensional Dynamics
- Federico Bonetto — Statistical Mechanics, Dynamical Systems
- Leonid Bunimovich
- Xu-Yan Chen
- Hannah Choi - Computational Neuroscience, Neural Networks, Neural Coding
- Luca Dieci — Numerical Methods, Dynamical Systems, Matrix Computation
- Albert Fathi
- Asaf Katz — Ergodic Theory, Measure Rigidity, Homogeneous Dynamics
- Rachel Kuske
- Michael Lacey — Fourier analysis, Weighted Inequalities
- Martin Short
- Molei Tao — Deep Learning, Optimization, Sampling, Measure Transport, Generative Modeling, AI4Science
- Chongchun Zeng
Geometry and Topology
- Igor Belegradek — Riemannian Geometry and Infinite Group Theory
- Greg Blekherman — Convex Geometry
- John Etnyre — Geometry and Low-dimensional Topology
- Albert Fathi
- Mohammad Ghomi — Differential Geometry and Topology
- Jennifer Hom
- Thang Le
- Galyna Livshyts
- Mike Wolf — Teichmuller Theory (classical and higher rank), Harmonic Maps, Minimal Surfaces
- Anton Zeitlin — Representation Theory with applications in Geometry, Topology, and Mathematical Physics
Mathematical Biology
- Greg Blekherman
- Leonid Bunimovich
- Hannah Choi - Computational Neuroscience, Neural Networks, Neural Coding
- Christine Heitsch
- Christian Houdré
Mathematical Physics
- Leonardo Abbrescia — Hyperbolic PDEs, Fluid Mechanics, Singularity formation, General Relativity
- Federico Bonetto — Statistical Mechanics, Dynamical Systems
- Leonid Bunimovich
- Plamen Iliev
- Michael Loss
- Ronghua Pan — Nonlinear PDEs, Fluid dynamics, General relativity
- Tobias Ried — Optimal Transport, Regularity Theory, Nonlinear PDEs, Quantum Mechanics, Disordered Systems
- Anton Zeitlin — Representation Theory with applications in Geometry, Topology, and Mathematical Physics
Probability and Statistics
- Leonid Bunimovich
- Michael Damron — Percolation, Particle systems
- Xiaoyu He — Discrete Probability
- Christian Houdré
- Vladimir Koltchinskii
- Michael Lacey — Fourier analysis, Weighted Inequalities
- Wenjing Liao — High Dimensional Data Analysis, Manifold Learning, Signal Processing
- Julia Lindberg - Algebraic Statistics
- Galyna Livshyts
- Cheng Mao — High-Dimensional Statistics, Machine Learning Theory, Applied Probability
- Heinrich Matzinger
- Benjamin McKenna — Random Matrices
- Tobias Ried — Optimal Transport, Regularity Theory, Nonlinear PDEs, Quantum Mechanics, Disordered Systems
- Martin Short
- Andrzej Swiech
- Molei Tao — Deep Learning, Optimization, Sampling, Measure Transport, Generative Modeling, AI4Science
- Mayya Zhilova
- Wei Zhu — (Scientific) Machine Learning, Statistical Learning Theory, Generative Models, and Optimization