Avi Feller Dept of Statistics Goldman School of Public Policy applied statistics, theoretical statistics, Bayesian statistics, machine learning, statistics in social sciences
Peng Ding Dept of Statistics Statistical causal inference, missing data, Bayesian statistics, applied statistics
Nikita Zhivotovskiy Dept of Statistics mathematical statistics, applied probability, statistical learning theory
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
Adityanand Guntuboyina Dept of Statistics nonparametric and high-dimensional statistics, shape constrained statistical estimation, empirical processes, statistical information theory
Michael Jordan Dept of Statistics Division of Computer Science (EECS) computer science, artificial intelligence, computational biology, statistics, machine learning, electrical engineering, applied statistics, optimization
Sanjam Garg Division of Computer Science (EECS) cryptography, cybersecurity, theoretical computer science
Perry de Valpine Dept of Environmental Science, Policy & Management population ecology, mathematical modeling and statistics
Rui Wang Dept of Chemical & Biomolecular Engineering theoretical polymer, soft materials, electrostatic double layer
Yun S. Song Dept of Statistics Division of Computer Science (EECS) computational biology, machine learning, applied probability and statistics
Deborah Nolan Dept of Statistics statistics, empirical process, high-dimensional modeling, technology in education
Nikhil Srivastava Dept of Mathematics theoretical computer science, random matrices, geometry of polynomials
Yasunori Nomura Dept of Physics quantum gravity, cosmology, Theoretical Particle Physics, quantum information
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
Elizabeth Purdom Dept of Statistics computational biology, bioinformatics, statistics, data analysis, sequencing, cancer genomics
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
Ahmed Alaa Computational Precision Health Program machine learning and artificial intelligence, health care, statistics
Eugene Chiang Dept of Astronomy Dept of Earth and Planetary Science planetary science, theoretical astrophysics, dynamics, planet formation, circumstellar disks
Ryan Giordano Dept of Statistics machine learning, variational inference, Bayesian methods, robustness quantification, applied statistics
Amanda Coston Dept of Statistics causal inference, machine learning, nonparametric statistics, responsible AI, algorithmic fairness