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
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
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
Anil Aswani Dept of Industrial Engineering & Operations Research machine learning and artificial intelligence, precision health, optimization, statistics
Ryan Giordano Dept of Statistics machine learning, variational inference, Bayesian methods, robustness quantification, applied statistics
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
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
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
Peter Bartlett
