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Research Expertise and Interest

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Name

Department

Dept of Industrial Engineering & Operations Research

stochastic and robust optimization, machine learning, online learning algorithms, transportation, Revenue Management, service system design

Alper Atamturk

Dept of Industrial Engineering & Operations Research

sparse learning, integer programming, computational optimization, robust optimization, logistics

Thibaut Mastrolia

Dept of Industrial Engineering & Operations Research

stochastic control, game theory, finance, optimization

Xin Guo

Dept of Industrial Engineering & Operations Research

stochastic control and games, theory of machine learning and applications to medical and financial data analysis, applied probability and stochastic models

Ying Cui

Dept of Industrial Engineering & Operations Research

continuous optimization, optimization under uncertainty, statistical estimations, machine learning, artificial intelligence

Max Willsey

Division of Computer Science (EECS)

programming optimization, programming languages

Javad Lavaei

Dept of Industrial Engineering & Operations Research

control theory, optimization, power systems

Rhonda Righter

Dept of Industrial Engineering & Operations Research

stochastic systems, service operations, scheduling and load balancing, telecommunications, computer and internet communications

Francesco Borrelli

Dept of Mechanical Engineering

automotive control systems, distributed and robust constrained control, manufacturing control systems, energy efficient buildings, model predictive control

Paul Grigas

Dept of Industrial Engineering & Operations Research

optimization, machine learning, data-driven decision-making

Carl Boettiger

Dept of Environmental Science, Policy & Management

theoretical ecology, stochastic processes, optimal control, decision theory, ecoinformatics, data science, tipping points

Satish Rao

Division of Computer Science (EECS)

combinatorial optimization, design and analysis of algorithms

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

Jay T. Groves

Dept of Chemistry

physical chemistry, intracellular signal transduction mechanisms, physical chemistry of cell membranes, single molecule imaging, stochastic processes

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

James Pitman

Dept of Statistics

fragmentation, statistics, mathematics, Brownian motion, distribution theory, path transformations, stochastic processes, local time, excursions, random trees, random partitions, processes of coalescence

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

Venkatesan Guruswami

Dept of Mathematics

Division of Computer Science (EECS)

theoretical computer science, coding theory, approximate optimization, randomness in computation, computational complexity

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