Jason Lee Dept of Statistics Division of Computer Science (EECS) machine learning theory, optimization, statistics, deep learning
Nikita Zhivotovskiy Dept of Statistics mathematical statistics, applied probability, statistical learning theory
Adityanand Guntuboyina Dept of Statistics nonparametric and high-dimensional statistics, shape constrained statistical estimation, empirical processes, statistical information theory
Mark van der Laan Dept of Statistics School of Public Health targeted learning, real-world data integration in RCTs, sequential adaptive designs, computational biology and genomics, censored data and survival analysis, medical research, inference in longitudinal studies
Ryan Giordano Dept of Statistics machine learning, variational inference, Bayesian methods, robustness quantification, applied statistics
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
Peter Bickel Dept of Statistics statistics, machine learning, semiparametric models, asymptotic theory, hidden Markov models, applications to molecular biology
Peter Bartlett Dept of Statistics Division of Computer Science (EECS) machine learning, statistical learning theory, adaptive control
Kannan Ramchandran Division of Computer Science (EECS) Division of Electrical Engineering (EECS) statistical and sparse signal processing, adversarial and distributed machine learning, coded computing, privacy and security, scalable distributed video-on-demand delivery, coding theory, communications, information theory, peer-to-peer networking, blockchains
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
Michael DeWeese Dept of Neuroscience Dept of Physics machine learning, computation, systems neuroscience, auditory cortex, neural coding, statistical mechanics
Michael Jordan Dept of Statistics Division of Computer Science (EECS) computer science, artificial intelligence, computational biology, statistics, machine learning, electrical engineering, applied statistics, optimization
Bin Yu Dept of Statistics machine learning, trustworthy data science and AI, interdisciplinary research in biomedicine, neuroscience, climate science
Dor Abrahamson School of Education mathematical cognition, design-based research, mixed-media design for mathematics learning environments, embodied interaction
Jennifer Chayes Dept of Mathematics Dept of Statistics Division of Computer Science (EECS) phase transitions in computer science, structural and dynamical properties of networks, graphons, machine learning, ethical decision making, climate change
Thomas Courtade Division of Electrical Engineering (EECS) information theory, probability, data compression, communications, computer science
Carl Boettiger Dept of Environmental Science, Policy & Management theoretical ecology, stochastic processes, optimal control, decision theory, ecoinformatics, data science, tipping points
Zoé Hamstead Dept of City & Regional Planning environmental planning, climate planning, sustainability and resilience, environmental and climate justice, geographic and spatial analysis, urban policy and political economy, global environmental governance, community engagement
Jacob Steinhardt
