Find UC Berkeley Faculty

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

Venkatesan Guruswami

Dept of Mathematics

Division of Computer Science (EECS)

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

Michael Jordan

Dept of Statistics

Division of Computer Science (EECS)

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

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

Max Willsey

Division of Computer Science (EECS)

programming optimization, programming languages

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

Ying Cui

Dept of Industrial Engineering & Operations Research

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

Satish Rao

Division of Computer Science (EECS)

combinatorial optimization, design and analysis of algorithms

Javad Lavaei

Dept of Industrial Engineering & Operations Research

control theory, optimization, power systems

Prasad Raghavendra

Division of Computer Science (EECS)

theory(THY), optimization, complexity theory, approximation algorithms

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

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

Bruno Olshausen

Dept of Neuroscience

School of Optometry

visual perception, computational neuroscience, computational vision

Anil Aswani

Dept of Industrial Engineering & Operations Research

machine learning and artificial intelligence, precision health, optimization, statistics

Sam Pimentel

Dept of Statistics

causal inference, health services & policy analysis, biostatistics, discrete optimization

Nir Yosef

Division of Computer Science (EECS)

computational biology

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

Ian Holmes

Dept of Bioengineering

computational biology, molecular evolution, computational genomics, Systems and Synthetic Biology

John Huelsenbeck

Dept of Integrative Biology

computational biology, evolutionary biology, phylogenetics

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