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
Alison Gopnik Dept of Psychology A.I., learning, philosophy, psychology, cognitive development, theory of mind, young children, children's causal knowledge, Bayes Net formalism
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
Biwen Zhang Haas School of Business capital markets, conflicts of interest, financial intermediation, machine learning
Manxi Wu Dept of Civil and Environmental Engineering game theory, multi-agent learning, transportation systems analysis
Anil Aswani Dept of Industrial Engineering & Operations Research machine learning and artificial intelligence, precision health, optimization, statistics
Ying Cui Dept of Industrial Engineering & Operations Research continuous optimization, optimization under uncertainty, statistical estimations, machine learning, artificial intelligence
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
Avi Feller Dept of Statistics Goldman School of Public Policy applied statistics, theoretical statistics, Bayesian statistics, machine learning, statistics in social sciences
Glynda Hull School of Education language, culture, society, education, literacy, writing in and out of schools, multi-media technology, new literacies, adult learning, work, community, school, university collaborations
David Bamman School of Information natural language processing, machine learning, digital humanities, computational social science, data science
Adrian Aguilera Computational Precision Health Program School of Social Welfare digital health, depression interventions, cognitive behavioral therapy, health equity, machine learning, implementation science
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
Alexandre Bayen Division of Electrical Engineering (EECS) control, optimization, machine learning, applications: transportation; mobile sensing; connected health
Maya L. Petersen School of Public Health Computational Precision Health Program causal inference, precision health, targeted learning, HIV, global health, pandemics
Park Sinchaisri Haas School of Business operations management, operations research, machine learning, human-computer interaction, decision-making, behavioral science, behavioral economics, service operations, applied econometrics
Alastair Iles Dept of Environmental Science, Policy & Management chemicals policy and politics, sustainable food systems, environmental STS, sustainability transitions, sustainability learning and societal change
Joshua Bloom Dept of Astronomy machine learning, gamma-ray bursts, supernovae, time-domain astronomy, data-driven discovery
Khalid M. Mosalam Dept of Civil and Environmental Engineering bridges, concrete and masonry structures, damage mechanics, earthquake engineering, fracture mechanics, machine learning
James W. Rector Dept of Civil and Environmental Engineering geoarchaeology, geophysics, acoustics, Seismology, machine learning, energy, carbon capture and storage, oil and gas
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
Alberto Sangiovanni-Vincentelli Division of Electrical Engineering (EECS) Cyber-Physical Systems, System design, Electronic Design Systems, embedded system design, control, integrated circuits, theory, Machine learning applications to Energy Efficient Building and Health
Bethany L. Goldblum Dept of Nuclear Engineering applied nuclear physics, neutron detection, scintillation physics, machine learning applications, nuclear weapon policy
Peter Bickel Dept of Statistics statistics, machine learning, semiparametric models, asymptotic theory, hidden Markov models, applications to molecular biology
Lexin Li
Lexin Li
Lexin Li
