Alper Atamturk Dept of Industrial Engineering & Operations Research sparse learning, integer programming, computational optimization, robust optimization, logistics
Xueyin (Snow) Zhang Dept of Philosophy Bayesian epistemology, decision theory, philosophy of probability, Chinese philosophy
Patrick Bradshaw School of Public Health epidemiologic methods, Bayesian methods, cancer epidemiology, cardiometabolic risk
Philip Marcus Dept of Mechanical Engineering algorithms, fluid mechanics, nonlinear dynamics, atmospheric flows, convection, ocean flows, numerical analysis, wind energy, Bayesian optimization, neural networks, turbulence, planet formation, internal gravity waves, inertial waves, desalination, protoplanetary disks
Ying Cui Dept of Industrial Engineering & Operations Research continuous optimization, optimization under uncertainty, statistical estimations, machine learning, artificial intelligence
Peng Ding Dept of Statistics Statistical causal inference, missing data, Bayesian statistics, applied statistics
Javad Lavaei Dept of Industrial Engineering & Operations Research control theory, optimization, power systems
Ryan Giordano Dept of Statistics machine learning, variational inference, Bayesian methods, robustness quantification, applied statistics
Thibaut Mastrolia Dept of Industrial Engineering & Operations Research stochastic control, game theory, finance, optimization
Satish Rao Division of Computer Science (EECS) combinatorial optimization, design and analysis of algorithms
Paul Grigas Dept of Industrial Engineering & Operations Research optimization, machine learning, data-driven decision-making
Avi Feller Dept of Statistics Goldman School of Public Policy applied statistics, theoretical statistics, Bayesian statistics, machine learning, statistics in social sciences
Joseph Lewnard School of Public Health infectious diseases, antimicrobial resistance, public health surveillance, mathematical modeling, Bayesian inference
Prasad Raghavendra Division of Computer Science (EECS) theory(THY), optimization, complexity theory, approximation algorithms
Ming Gu Dept of Mathematics mathematics, scientific computing, numerical linear algebra, convex optimization
Boubacar Kante Division of Electrical Engineering (EECS) optoelectronics, quantum optics, optimization, Antennas, Biophysics and Sensing
Sam Pimentel Dept of Statistics causal inference, health services & policy analysis, biostatistics, discrete optimization
Anil Aswani Dept of Industrial Engineering & Operations Research machine learning and artificial intelligence, precision health, optimization, statistics
Rajan Udwani Dept of Industrial Engineering & Operations Research algorithms, optimization under uncertainty, Revenue Management, pricing, online platforms
Scott Moura Dept of Civil and Environmental Engineering control systems, optimization, data science, batteries, electric vehicles, energy systems
Michael J. Lindsey Dept of Mathematics applied mathematics, mathematical analysis, probability, numerical analysis, optimization, Monte Carlo methods
Duncan Callaway Dept of Energy & Resources Group Division of Electrical Engineering (EECS) energy systems analysis, grid decarbonization, modeling and control and optimization for electric power systems
Alexandre Bayen Division of Electrical Engineering (EECS) control, optimization, machine learning, applications: transportation; mobile sensing; connected health
Alper Atamturk
