Stats Faculty Regular

Assistant Professor, Hydrology and Atmospheric Sciences

Research interests include computational hydrology, with a focus on deep learning, physically based models and hybrid differentiable models. Also scientific computing and open science.

Professor and Department Head, Physiology

The Liang group studies molecular systems medicine. e. The current work in our group focuses on three areas: (epi)genomics and precision medicine, regulatory RNA, and cellular metabolism, as they relate to hypertension, cardiovascular and kidney disease.

Associate Professor, Pharmacy Practice and Science

Assistant Professor, Mathematics

spatiotemporal statistics; Bayesian statistics; Ecological applications

Assistant Professor, Animal & Comparative Biomedical Sciences

Multidisciplinary approach to study the dynamics of zoonotic infectious diseases. We develop computational, mathematical and data-driven models to understand the ecology and evolution of infectious diseases at the wildlife, livestock and human interface.

Associate Professor - School of Plant Sciences

​​Our​ research is motivated by the threads that climate change imposes on the agricultural and natural plant ecosystem. Therefore, we develop imaging and simulation approaches to understand the function of natural variation in plants

Associate Professor, Epidemiology and Biostatistics

Dr. Lin has worked extensively on statistical methods for meta-analysis, network meta-analysis of multiple-treatment comparisons, publication bias, and Bayesian methods. He is also interested in the applications of statistical methods to real-world proble

Assistant Research Professor, R Ken Coit College of Pharmacy

Statistical genetics and genomics, including computational methods for analyzing large-scale sequencing data, rare variant association analysis, genomics-driven drug target discovery and precision medicine

Assistant professor of Epidemiology and Biostatistics

Dimension reduction and variable selection, big data analytics, data integration

Assistant Professor of Systems and Industrial Engineering

Research is focused on the design, analysis, and implementation of stochastic approximation methods for solving convex optimization and stochastic variational inequality problems with applications in machine learning, game theory, and power systems.