Faculty

Research Interests: Optimization, Machine learning theory, High-dimensional statistics, Causal inference

Research Interests: Connection between optimization, MCMC sampling, dynamical system, interacting particle system; Blending machine learning with traditional numerical algorithms for: PDE, sampling, optimal transport, control; AI4Science: data-driven approaches to computational problems arising in physics & chemistry

Research Interests: High Dimensional CLT, Strong Approximation, Dependent Data, Factor models, Casual inference.

Research Interests: use of non-traditional sources of data to study problems in data-scarce settings, with a focus on conflict, crime and the developing world.

Research Interests:  Practical and theoretical Bayesian statistics with application to public health and medicine, demography, environmental data, small area estimation, official statistics, fMRI and survey sampling data, among others.

Research Interests: Manifold learning, deep learning, and large foundation models; High-dimensional statistics and applied random matrix theory; Non-stationary time series analysis; Applications in biological and medical sciences

Research Interests: Deep Learning, Conformal Inference, Causal Inference, Functional and Longitudinal Data Analysis, Survival Analysis

Research Interests: Statistical and Scientific Computing, R/S Data Analysis Environments, Programming Language Design, Software Infrastructure and Engineering, Meta-programming, Dynamic graphics, Reproducible Research Tools, Statistical Education

Research Interests: Covariance Estimation, Graphical models, High dimensional inference, Bayesian methods, Environmental Statistics, Positivity