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Research Expertise and Interest

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Name

Department

Negar Mehr

Dept of Mechanical Engineering

robotics, control theory, artificial intelligence, game theory, machine learning

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

Joshua Blumenstock

School of Information

machine learning, development economics, poverty and public policy, inequality and crisis

Amanda Coston

Dept of Statistics

causal inference, machine learning, nonparametric statistics, responsible AI, algorithmic fairness

John Wright

Division of Computer Science (EECS)

quantum state learning, quantum complexity theory, property testing, approximation algorithms

Mohammad Reza Kaazempur Mofrad

Dept of Bioengineering

Dept of Mechanical Engineering

molecular cell biomechanics, bacterial communities / microbiomes, deep learning for biology and medicine

Eileen D. Gambrill

School of Social Welfare

social welfare, professional ethics and education, social learning theory, behavioral methods

Jose M. Carmena

Division of Electrical Engineering (EECS)

brain-machine interfaces, neural ensemble computation, neuroprosthetics, sensorimotor learning and control

Deirdre Mulligan

School of Information

information policy, law, privacy, security, machine learning and artificial intelligence

Lin Lin

Dept of Mathematics

applied mathematics, Quantum Chemistry, quantum computation, Scientific machine learning

David Bamman

School of Information

natural language processing, machine learning, digital humanities, computational social science, data science

Maya L. Petersen

Computational Precision Health Program

School of Public Health

causal inference, precision health, Health AI, targeted learning, HIV, global health, pandemics

Alane Suhr

Division of Computer Science (EECS)

artificial intelligence, natural language processing, machine learning, computer vision, computational linguistics

Jingshen Wang

School of Public Health

precision medicine, causal inference, adaptive experiment, machine learning and artificial intelligence

Michael DeWeese

Dept of Neuroscience

Dept of Physics

machine learning, computation, systems neuroscience, auditory cortex, neural coding, statistical mechanics

Nika Haghtalab

Division of Computer Science (EECS)

artificial intelligence, machine learning, theoretical computer science, game theory and mechanism design

Alan Hubbard

School of Public Health

causal inference, targeted learning, statistical issues in epidemiology, precision medicine and public health

Bin Yu

Dept of Statistics

machine learning, trustworthy data science and AI, interdisciplinary research in biomedicine, neuroscience, climate science

Alexandre Bayen

Division of Electrical Engineering (EECS)

control, optimization, machine learning, applications: transportation; mobile sensing; connected health

Ryan Giordano

Dept of Statistics

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

Alexei Efros

Division of Computer Science (EECS)

computer vision, computer graphics, computational photography, machine learning, artificial intelligence

Irene Chen

Computational Precision Health Program

Division of Computer Science (EECS)

machine learning, personalized medicine and healthcare systems, global health equity, precision health

Ying Cui

Dept of Industrial Engineering & Operations Research

continuous optimization, optimization under uncertainty, statistical estimations, machine learning, artificial intelligence

Avi Feller

Dept of Statistics

Goldman School of Public Policy

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

Armando Fox

Division of Computer Science (EECS)

online education, MOOC, blended learning, parallel programming, software engineering, Web development

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