Amanda Coston Dept of Statistics causal inference, machine learning, nonparametric statistics, responsible AI, algorithmic fairness
Joshua Blumenstock School of Information machine learning, development economics, poverty and public policy, inequality and crisis
Bin Yu Dept of Statistics machine learning, trustworthy data science and AI, interdisciplinary research in biomedicine, neuroscience, climate science
John Wright Division of Computer Science (EECS) quantum state learning, quantum complexity theory, property testing, approximation algorithms
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
Lin Lin Dept of Mathematics applied mathematics, Quantum Chemistry, quantum computation, Scientific machine learning
Deirdre Mulligan School of Information information policy, law, privacy, security, machine learning and artificial intelligence
Michael DeWeese Dept of Neuroscience Dept of Physics machine learning, computation, systems neuroscience, auditory cortex, neural coding, statistical mechanics
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
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
Alexandre Bayen Division of Electrical Engineering (EECS) control, optimization, machine learning, applications: transportation; mobile sensing; connected health
Alexei Efros Division of Computer Science (EECS) computer vision, computer graphics, computational photography, machine learning, artificial intelligence
Ryan Giordano Dept of Statistics machine learning, variational inference, Bayesian methods, robustness quantification, applied statistics
Maya L. Petersen School of Public Health Computational Precision Health Program causal inference, precision health, targeted learning, HIV, global health, pandemics
Irene Chen Computational Precision Health Program Division of Computer Science (EECS) machine learning, personalized medicine and healthcare systems, global health equity, precision health
Teresa Head-Gordon Dept of Bioengineering Dept of Chemical & Biomolecular Engineering Dept of Chemistry Computational chemistry, machine learning, chemical physics, biophysics, biomolecules, materials, catalysis, computational science
Heather Gray Dept of Physics particle physics, machine learning, algorithms, quantum algorithms, general purpose computation on the GPU (GPGPU)
Armando Fox Division of Computer Science (EECS) online education, MOOC, blended learning, parallel programming, software engineering, Web development
Dor Abrahamson School of Education mathematical cognition, design-based research, mixed-media design for mathematics learning environments, embodied interaction
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
Daniel Siefman Dept of Nuclear Engineering neutronics, criticality safety, nuclear data validation, machine learning, neutron noise, reactor dosimetry
Amanda Coston
Amanda Coston
Amanda Coston
