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
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
Priya Moorjani Dept of Molecular & Cell Biology Human evolutionary genetics, human genetics, ancient DNA, population genetics, statistical genetics
Ian Wang Dept of Environmental Science, Policy & Management genetics and genomics, genomics, landscape genetics, evolution, population genetics, conservation, herpetology, GIS, spatial analysis, statistical methods, epigenetics
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
Adityanand Guntuboyina Dept of Statistics nonparametric and high-dimensional statistics, shape constrained statistical estimation, empirical processes, statistical information theory
Elizabeth Purdom Dept of Statistics computational biology, bioinformatics, statistics, data analysis, sequencing, cancer genomics
Craig Miller Dept of Molecular & Cell Biology genetics, developmental biology, evolutionary biology, evolution, quantitative genetics, developmental genetics, evolutionary genetics, craniofacial development
Michael Jordan Dept of Statistics Division of Computer Science (EECS) computer science, artificial intelligence, computational biology, statistics, machine learning, electrical engineering, applied statistics, optimization
Avi Feller Dept of Statistics Goldman School of Public Policy applied statistics, theoretical statistics, Bayesian statistics, machine learning, statistics in social sciences
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
Rachel Brem Dept of Plant and Microbial Biology molecular evolution, ecological genetics, genetics and genomics, fungal genetics
Ryan Tibshirani Dept of Statistics statistical computing, applications in public health, high-dimensional data analysis, nonparametric inference, artificial intelligence, machine learning
Peter Bickel Dept of Statistics statistics, machine learning, semiparametric models, asymptotic theory, hidden Markov models, applications to molecular biology
Ryan Giordano Dept of Statistics machine learning, variational inference, Bayesian methods, robustness quantification, applied statistics
Peter Sudmant Dept of Integrative Biology genomics, genetics, computational biology, structural variation, RNA, diversity, aging, population genetics
Deborah Nolan Dept of Statistics statistics, empirical process, high-dimensional modeling, technology in education
Yun S. Song Dept of Statistics Division of Computer Science (EECS) computational biology, machine learning, applied probability and statistics
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
Amanda Coston Dept of Statistics causal inference, machine learning, nonparametric statistics, responsible AI, algorithmic fairness
Haiyan Huang
Haiyan Huang
Haiyan Huang
