Haiyan Huang Dept of Statistics applied statistics, functional genomics, translational bioinformatics, high dimensional and integrative genomic/genetic data analysis, network modeling, hierarchical multi-lable classification
Adityanand Guntuboyina Dept of Statistics nonparametric and high-dimensional statistics, shape constrained statistical estimation, empirical processes, statistical information theory
Amanda Coston Dept of Statistics causal inference, machine learning, nonparametric statistics, responsible AI, algorithmic fairness
Deborah Nolan Dept of Statistics statistics, empirical process, high-dimensional modeling, technology in education
Nikita Zhivotovskiy Dept of Statistics mathematical statistics, applied probability, statistical learning 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
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
Michael Jordan Dept of Statistics Division of Computer Science (EECS) computer science, artificial intelligence, computational biology, statistics, machine learning, electrical engineering, applied statistics, optimization
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
Ryan Giordano Dept of Statistics machine learning, variational inference, Bayesian methods, robustness quantification, applied statistics
Yun S. Song Dept of Statistics Division of Computer Science (EECS) artificial intelligence, machine learning, applied probability and statistics, computational biology, computational genomics, human genetics
Rasmus Nielsen Dept of Integrative Biology Dept of Statistics evolution, molecular evolution, population genetics, human variation, human genetics, phylogenetics, applied statistics, genetics, evolutionary processes, evolutionary biology
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
Ahmed Alaa Computational Precision Health Program machine learning and artificial intelligence, health care, statistics
Ilan Adler Dept of Industrial Engineering & Operations Research mathematical programming, computational game theory, applied probability
Anil Aswani Dept of Industrial Engineering & Operations Research machine learning and artificial intelligence, precision health, optimization, statistics
Manisha Shah Dept of Agricultural & Resource Economics applied microeconomics, international development, global health, gender
Franziska Weber Dept of Mathematics applied mathematics, mathematical analysis, numerical analysis, nonlinear partial differential equations
Sofia Villas-Boas Dept of Agricultural & Resource Economics economics, industrial organization and applied econometrics, agricultural & resource economics, consumer behavior and decision making
Sophia Rabe-Hesketh School of Education biostatistics, educational statistics, latent variable models, missing data methods, multilevel models, generalized linear latent and mixed models, hierarchical models, longitudinal data, Item response models, structural equation models
Will Fithian
Will Fithian
Will Fithian
