Faculty

The RTG is an equal partnership between the Departments of Statistics and Mathematics, and includes faculty from the Biomathematics program, which integrates both disciplines.

Core faculty (co-PIs):

  • Brian Reich (Distinguished Prof, Stat) conducts research in Bayesian models for environmental and epidemiological applications that combine statistical and mechanistic models.
  • Mette Olufsen (Prof, Math) conducts research in biomathematics with a focus on physiology, including devising patient-specific models integrating imaging and dynamics data.
  • Erin Schliep (Assoc Prof, Stat) conducts interdisciplinary research developing statistical methods and models to study complex ecological processes and their responses to climate change.
  • Kevin Flores (Assoc Prof, Math) develops forecasting and UQ methods that hybridize machine learning and mathematical modeling, and has recently developed methods to learn differential equations models from noisy biological data.

Senior investigators:

  • Alen Alexanderian (Assoc Prof, Math) develops numerical methods for inverse problems, optimization under uncertainty, sensitivity analysis, and Bayesian inference.
  • Annie Sauer Booth (Assist Prof, Stat) develops new statistical methods for UQ including Bayesian optimization, and fusing of deep learning with Gaussian process models to calibrate, emulate, and optimize complex computer models.
  • Mohammad Farazmand (Assist Prof, Math) works on inference, prediction, and mitigation of rare extreme events in dynamical systems with application to real-world problems such as ocean rogue waves, turbulence, wildfires, and climate transitions.
  • Sujit Ghosh (Prof, Stat) studies foundational and theoretical aspects of Bayesian methodology and applies these methods to environmental data and calibration of mathematical models.
  • Emily Griffith (Assoc Prof of the Practice, Stat) is involved in collaborative data science research and serves as the Director of Consulting for the Data Science Academy, where she develops best practices for training students to be interdisciplinary data scientists.
  • Mansoor Haider (Data Science Program Director & Prof Math) applies computational mathematics to life sciences and public health, including modeling of biological soft tissues and unsupervised matching learning algorithms for public health applications.
  • Radmila Sazdanovic (Assoc Prof. Math) is an expert in categorification, low dimensional and applied algebraic topology, and life-science applications.