Faculty

Commodity markets Mathematical finance Dynamical systems Geometry

Image analysis statistical learning bioinformatics

Financial mathematics Commodities

Macroeconometrics Forecasting

Discrete mathematics Graph theory Multilinear algebra Image analysis Experimental math

Dimensionality reduction Graph-based nonparametric estimation High-dimensional regression Hypothesis testing

Design and analysis of algorithms for continuous optimization problems beyond the limited areas where classical theory applies

Artificial intelligence Large-scale systems Statistical machine learning Theory and methodology of deep learning

Algebraic combinatorics Lattice polytopes Cluster algebras

Fractal geometry Probability Dynamical systems

Algorithms, data, and the computer-assisted modeling of complex dynamical systems

Probability Statistics Mathematical data science Convex optimization Discrete mathematics

Applied statistics Shape analysis Pattern theory Medical imaging

Machine learning Data science Probability

Theory and applications of convex and non-convex optimization in large-scale machine learning and data science problems

Analysis Partial differential equations Algebraic topology Big data Data intensive computation Harmonic analysis over manifolds and over discrete structures

Mathematical image processing Shape analysis Variational methods Applied statistics Mathematical 3D printing

Financial mathematics Equity derivative trading and risk management Number theory

Statistics Computational probability Bioinformatics

Math of data science Stochastic and convex geometry Point processes High dimensional probability Statistical learning theory

Computational statistics kernel and mixture estimates statistical pattern recognition statistical image analysis dimensionality reduction model selection statistical inference for high-dimensional and graph data.

Large-scale graph machine learning Graph neural networks Signal processing Data science

Image processing Mathematical modeling (partial differential equations) Inverse problems (differential equations) Machine learning Optimal experiment design Photonics

Discrete Mathematics  Partially Ordered Sets  Random Methods  Graph Theory

Stochastic systems Parameter estimation Stochastic optimization Monte Carlo methods and simulation Neural networks Control systems System identification and Kalman filtering Mathematical statistics Optimization theory Uncertainty calculation

Stochastic processes Asymptotics and partial differential equations

Optimization for data science machine learning and optimization representation learning graph neural networks

Probability Stochastic processes Statistics Discrete mathematics Percolation theory Random graphs

Statistics Machine learning Nonparametric Bayes Reinforcement learning clinical trial designs Infectious disease (e.g., HIV) Electronic health/medical data.

Dynamical systems Fluid dynamics Kinetic theory Partial differential equations Partial regularity Robust optimization

Statistical Properties of Markov Random Fields  Image Analysis Deformation Analysis Shape Recognition