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Research Expertise and Interest

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Name

Department

political economy, ethnic politics, comparative clientelism in developing countries, research design, causal inference, statistical methods, multi-method research

K. Birgitta Whaley

Dept of Chemistry

quantum information and quantum computation, control and simulation of complex quantum systems, quantum effects in biological systems, quantum physics, quantum mechanics

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

M. Reza Alam

Dept of Mechanical Engineering

Theoretical Fluid Dynamics, Nonlinear Wave Mechanics, ocean and coastal waves phenomena, ocean renewable energy (wave, Tide and Offshore Wind Energy), Nonlinear Dynamical Systems, Fluid Flow Control, ocean renewable energy

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

Raphael Bousso

Dept of Physics

physics, quantum mechanics, gravity, unified description of nature, string theory, quantum properties of black holes, the geometry of spacetime, covariant entropy bound, cosmological constant

Daniel Klein

Division of Computer Science (EECS)

unsupervised language acquisition, efficient algorithms for NLP, linguistically rich models of language, integrating symbolic and statistical methods for NLP, organization of the web, machine translation, information extraction

James A. Sethian

Dept of Mathematics

mathematics, applied mathematics, partial differential equations, computational physics, level set Methods, computational fluid mechanics and materials sciences, fast marching methods

Avi Feller

Dept of Statistics

Goldman School of Public Policy

applied statistics, theoretical statistics, Bayesian statistics, machine learning, statistics in social sciences

Henry Brady

Dept of Political Science

Goldman School of Public Policy

comparative politics, public policy, electoral politics, political participation, survey research, program evaluation, statistical methods in the social sciences, social welfare policy, Soviet Union, inequality in America

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

Michael Jordan

Dept of Statistics

Division of Computer Science (EECS)

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

Philip Marcus

Dept of Mechanical Engineering

algorithms, fluid mechanics, nonlinear dynamics, atmospheric flows, convection, ocean flows, numerical analysis, wind energy, Bayesian optimization, neural networks, turbulence, planet formation, internal gravity waves, inertial waves, desalination, protoplanetary disks

Michael Manga

Dept of Earth and Planetary Science

hydrogeology, fluid mechanics, geomorphology, earth & planetary science, geological processes involving fluids, including problems in physical volcanology, geodynamics, dynamics of suspensions, flow & transport in porous materials, percolation theory

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

Will Fithian

Dept of Statistics

Theoretical and Applied Statistics

Lexin Li

School of Public Health

neuroimaging data analysis, deep brain stimulation, brain-computer-interface, statistical machine learning, Deep Learning, reinforcement learning, networks data analysis, functional data analysis, tensor analysis, ordinary differential equations, dimension reduction, high dimensional inference

Song Mei

Dept of Statistics

data science, statistics, machine learning

Fotini Chow

Dept of Civil and Environmental Engineering

environmental fluid mechanics, wind energy applications, clouds, large-eddy simulation, turbulence modeling, atmospheric boundary layer flow, flow over complex terrain, wildfire smoke transport, methane emissions, urban dispersion modeling, urban air quality

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)

computational biology, machine learning, applied probability and statistics

Deborah Nolan

Dept of Statistics

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

Elizabeth Purdom

Dept of Statistics

computational biology, bioinformatics, statistics, data analysis, sequencing, cancer genomics

Perry de Valpine

Dept of Environmental Science, Policy & Management

population ecology, mathematical modeling and statistics

Peter Bickel

Dept of Statistics

statistics, machine learning, semiparametric models, asymptotic theory, hidden Markov models, applications to molecular biology

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