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Research Expertise and Interest

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Name

Department

Peter Bartlett

Dept of Statistics

Division of Computer Science (EECS)

machine learning, statistical learning theory, adaptive control

Jennifer Listgarten

Division of Computer Science (EECS)

artificial intelligence, machine learning, computational biology, protein engineering, statistical design of experiments, statistical machine learning, experimental design

Sandrine Dudoit

Dept of Statistics

School of Public Health

statistics, machine learning, data science, applied statistics, statistical computing, computational biology, computational genomics, precision medicine, precision health

Nikita Zhivotovskiy

Dept of Statistics

mathematical statistics, applied probability, statistical learning theory

Michael DeWeese

Dept of Neuroscience

Dept of Physics

machine learning, computation, systems neuroscience, auditory cortex, neural coding, statistical mechanics

Song Mei

Dept of Statistics

data science, statistics, machine learning

Ying Cui

Dept of Industrial Engineering & Operations Research

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

Ryan Tibshirani

Dept of Statistics

statistical computing, applications in public health, high-dimensional data analysis, nonparametric inference, artificial intelligence, machine learning

Ahmed Alaa

Computational Precision Health Program

machine learning and artificial intelligence, health care, statistics

Uros Seljak

Dept of Physics

astrophysics, cosmology, machine learning, Bayesian statistics

Yun S. Song

Dept of Statistics

Division of Computer Science (EECS)

computational biology, machine learning, applied probability and statistics

Avi Feller

Dept of Statistics

Goldman School of Public Policy

applied statistics, theoretical statistics, Bayesian statistics, machine learning, statistics in social sciences

Amanda Coston

Dept of Statistics

causal inference, machine learning, nonparametric statistics, responsible AI, algorithmic fairness

Ryan Giordano

Dept of Statistics

machine learning, variational inference, Bayesian methods, robustness quantification, applied statistics

Anil Aswani

Dept of Industrial Engineering & Operations Research

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

Jacob Steinhardt

Dept of Statistics

artificial intelligence, machine learning

Michael Jordan

Dept of Statistics

Division of Computer Science (EECS)

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

Nilah Ioannidis

Division of Computer Science (EECS)

computational biology, machine learning, artificial intelligence, genomics, personal genome interpretation, precision health, rare diseases, statistical genetics, molecular biology, biophysics

Vira Semenova

Dept of Economics

econometrics, machine learning

Christian Borgs

Division of Computer Science (EECS)

theoretical computer science, probability theory, combinatorics, complex networks, statistical physics, artificial intelligence, applications of artificial intelligence and machine learning in engineering and sciences

Pieter Abbeel

Division of Computer Science (EECS)

robotics, machine learning, artificial intelligence, Deep Learning

Peter Bickel

Dept of Statistics

statistics, machine learning, semiparametric models, asymptotic theory, hidden Markov models, applications to molecular biology

Kurt Keutzer

Division of Electrical Engineering (EECS)

computationally efficient machine learning and deep learning, AI

Angjoo Kanazawa

Division of Computer Science (EECS)

CS-vision, graphics, machine learning

Lexin Li

School of Public Health

neuroimaging data analysis, deep brain stimulation, brain-computer-interface, statistical machine learning, Deep Learning, reinforcement learning, networks data analysis, functional data analysis, tensor analysis, ordinary differential equations, dimension reduction, high dimensional inference

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