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Research Expertise and Interest

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Name

Department

Alper Atamturk

Dept of Industrial Engineering & Operations Research

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

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

Thibaut Mastrolia

Dept of Industrial Engineering & Operations Research

stochastic control, game theory, finance, optimization

Paul Grigas

Dept of Industrial Engineering & Operations Research

optimization, machine learning, data-driven decision-making

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

Boubacar Kante

Division of Electrical Engineering (EECS)

optoelectronics, quantum optics, optimization, Antennas, Biophysics and Sensing

Ming Gu

Dept of Mathematics

mathematics, scientific computing, numerical linear algebra, convex optimization

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

Scott Moura

Dept of Civil and Environmental Engineering

control systems, optimization, data science, batteries, electric vehicles, energy systems

Rajan Udwani

Dept of Industrial Engineering & Operations Research

algorithms, optimization under uncertainty, Revenue Management, pricing, online platforms

Michael J. Lindsey

Dept of Mathematics

applied mathematics, mathematical analysis, probability, numerical analysis, optimization, Monte Carlo methods

Venkatesan Guruswami

Dept of Mathematics

Division of Computer Science (EECS)

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

Alexandre Bayen

Division of Electrical Engineering (EECS)

control, optimization, machine learning, applications: transportation; mobile sensing; connected health

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

Huiwen Jia

Dept of Industrial Engineering & Operations Research

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

Aditi Krishnapriyan

Dept of Chemical & Biomolecular Engineering

Division of Computer Science (EECS)

machine learning, geometric deep learning, differentiable physics, dynamical systems, numerical methods, computational geometry, optimization

Dorit Hochbaum

Dept of Industrial Engineering & Operations Research

data mining, integer programming, discrete optimization, network flow techniques, clustering, image segmentation, machine vision, pattern recognition

Michael Jordan

Dept of Statistics

Division of Computer Science (EECS)

computer science, artificial intelligence, computational biology, statistics, machine learning, electrical engineering, applied statistics, optimization

Alistair Sinclair

Dept of Statistics

Division of Electrical Engineering (EECS)

algorithms, applied probability, statistics, random walks, Markov chains, computational applications of randomness, Markov chain Monte Carlo, statistical physics, combinatorial optimization

Shmuel S. Oren

Dept of Industrial Engineering & Operations Research

economics, algorithms, financial engineering, risk management, planning, optimization, operation of electric power systems, market based coordination of network systems, trading instruments

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

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