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Research Expertise and Interest

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Name

Department

Will Fithian

Dept of Statistics

Theoretical and Applied Statistics

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

Michael Jordan

Dept of Statistics

Division of Computer Science (EECS)

computer science, artificial intelligence, computational biology, statistics, machine learning, electrical engineering, applied statistics, optimization

Ryan Giordano

Dept of Statistics

machine learning, variational inference, Bayesian methods, robustness quantification, applied statistics

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

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

Woman with dark hair wearing gray blazer and glasses - smiling

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

David Limmer

Dept of Chemistry

theoretical chemistry

Adityanand Guntuboyina

Dept of Statistics

nonparametric and high-dimensional statistics, shape constrained statistical estimation, empirical processes, statistical information theory

Song Mei

Dept of Statistics

data science, statistics, machine learning

Sanjam Garg

Division of Computer Science (EECS)

cryptography, cybersecurity, theoretical computer science

Bingqing Cheng

Dept of Chemistry

theoretical chemistry, physical chemistry, polymers and nanoscience

Rui Wang

Dept of Chemical & Biomolecular Engineering

theoretical polymer, soft materials, electrostatic double layer

Perry de Valpine

Dept of Environmental Science, Policy & Management

population ecology, mathematical modeling and statistics

Jason Lee

Dept of Statistics

Division of Computer Science (EECS)

machine learning theory, optimization, statistics, deep learning

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

Deborah Nolan

Dept of Statistics

statistics, empirical process, high-dimensional modeling, technology in education

Ahmed Alaa

Computational Precision Health Program

machine learning and artificial intelligence, health care, statistics

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

Uros Seljak

Dept of Physics

astrophysics, cosmology, machine learning, Bayesian statistics

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