Algebra
- Matt Baker — Number Theory, Arithmetic Geometry, Combinatorics
- Greg Blekherman — Applied and Real Algebraic Geometry
- Ernie Croot
- Plamen Iliev
- Anton Leykin — Computational Algebraic Geometry
- Dan Margalit — Moduli Spaces
- Josephine Yu
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
- 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
- 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 — Sampling & Optimization, Deep Learning, (Stochastic) Dynamics, (Multiscale/Geometric+Scientific) Computing
- Haomin Zhou
Differential Equations
- 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
- Rafael de la Llave
- Ronghua Pan — Nonlinear PDEs, Fluid Dynamics, General Relativity
- Andrzej Swiech
- Molei Tao — Sampling & Optimization, Deep Learning, (Stochastic) Dynamics, (Multiscale/Geometric+Scientific) Computing
- Chongchun Zeng
- Haomin Zhou
Discrete Mathematics
- Matt Baker — Number Theory, Arithmetic Geometry, Combinatorics
- Anton Bernshteyn — Graph Theory, Descriptive Set Theory with Applications in Dynamics
- Greg Blekherman
- Ernie Croot
- Christine Heitsch
- Christian Houdré
- Tom Kelly
- Anton Leykin — Computational Algebraic Geometry
- Galyna Livshyts
- Molei Tao — Sampling & Optimization, Deep Learning, (Stochastic) Dynamics, (Multiscale/Geometric+Scientific) Computing
- Xingxing Yu
- Josephine Yu
Dynamical Systems
- Anton Bernshteyn — Graph Theory, Descriptive Set Theory with Applications in Dynamics
- 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
- Rachel Kuske
- Michael Lacey — Fourier analysis, Weighted Inequalities
- Rafael de la Llave
- Dan Margalit — Complex Dynamics
- Martin Short
- Molei Tao — Sampling & Optimization, Deep Learning, (Stochastic) Dynamics, (Multiscale/Geometric+Scientific) Computing
- 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
- Dan Margalit — Geometric Group Theory & Low-dimensional Topology
Mathematical Biology
- Greg Blekherman
- Leonid Bunimovich
- Hannah Choi - Computational Neuroscience, Neural Networks, Neural Coding
- Christine Heitsch
- Christian Houdré
Mathematical Physics
- Federico Bonetto — Statistical Mechanics, Dynamical Systems
- Leonid Bunimovich
- Plamen Iliev
- Rafael de la Llave
- Michael Loss
- Ronghua Pan — Nonlinear PDEs, Fluid dynamics, General relativity
Probability and Statistics
- Leonid Bunimovich
- Michael Damron — Percolation, Particle systems
- Christian Houdré
- Vladimir Koltchinskii
- Michael Lacey — Fourier analysis, Weighted Inequalities
- Wenjing Liao — High Dimensional Data Analysis, Manifold Learning, Signal Processing
- Galyna Livshyts
- Cheng Mao — High-Dimensional Statistics, Machine Learning Theory, Applied Probability
- Heinrich Matzinger
- Martin Short
- Andrzej Swiech
- Molei Tao — Sampling & Optimization, Deep Learning, (Stochastic) Dynamics, (Multiscale/Geometric+Scientific) Computing
- Mayya Zhilova