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Research Expertise and Interest

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Name

Department

Biwen Zhang

Haas School of Business

capital markets, conflicts of interest, financial intermediation, machine learning

Amanda Coston

Dept of Statistics

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

Negar Mehr

Dept of Mechanical Engineering

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

Claire Tomlin

Division of Computer Science (EECS)

Division of Electrical Engineering (EECS)

electrical engineering, computer sciences, control, biosystems, control theory, intelligent systems, robotics, hybrid and embedded systems, biological cell networks

Jelani Nelson

Division of Computer Science (EECS)

theory, algorithms, streaming algorithms, dimensionality reduction, randomized algorithms, machine learning, privacy

Deirdre Mulligan

School of Information

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

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

Lin Lin

Dept of Mathematics

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

Alastair Iles

Dept of Environmental Science, Policy & Management

chemicals policy and politics, sustainable food systems, environmental STS, sustainability transitions, sustainability learning and societal change

Clark Nguyen

Division of Electrical Engineering (EECS)

electrical engineering, computer sciences, integrated circuits, sensors, micro electromechanical systems, signal processors, frequency control, RF communications, micromachining technology

Maya L. Petersen

Computational Precision Health Program

School of Public Health

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

Alexandre Bayen

Division of Electrical Engineering (EECS)

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

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

Alan Hubbard

School of Public Health

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

Ian Duncan

Dept of English

English, the novel, British literature 1750-1900, Scottish literature, history and theory of fiction, Scottish enlightenment/romanticism, Scott, literature and the human sciences, Darwin

Ying Cui

Dept of Industrial Engineering & Operations Research

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

Dor Abrahamson

School of Education

mathematical cognition, design-based research, mixed-media design for mathematics learning environments, embodied interaction

Ryan Giordano

Dept of Statistics

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

Daniel Siefman

Dept of Nuclear Engineering

neutronics, criticality safety, nuclear data validation, machine learning, neutron noise, reactor dosimetry

Dana Miller-Cotto

School of Education

educational equity, early childhood education, cognitive processes, early math learning, social contexts of education

Picture of Professor Gray outside the physics department.

Heather Gray

Dept of Physics

particle physics, machine learning, algorithms, quantum algorithms, general purpose computation on the GPU (GPGPU)

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

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