Affiliated Faculty

MIDAS works to foster interdisciplinary research collaboration across campus with our community of 550 affiliate faculty members, who come from over 60 U-M departments, and include instructional (tenure / tenure track / lecturer), clinical and research track faculty.

Use this box to search by name, department, or other keyword. Use the filters below to search by major data science methodologies or applications.




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Deanna Isaman

chronic disease, data synthesis, economic model

Christiane Jablonowski

Physics-guided machine learning, climate modeling, emulation

Abigail Jacobs

Computational social science, empirical design, governance, observational data, social networks, statistical inference

H. V. Jagadish

Database systems, query models and analytics processes for reliable insight
Meha Jain

Meha Jain

agriculture, machine learning, remote sensing, sustainability

Stefanus Jasin

approximation algorithm, business analytics, machine learning, optimization

Hui Jiang

Bioinformatics, computational statistics, machine learning, optimization, statistical genomics

Ruiwei Jiang

Data-Driven Optimization, Electric Power System, Robust Optimization, Stochastic Optimization, Transportation, healthcare

Judy Jin

Data fusion for improving system operation and quality
Sean Johnson

Sean Johnson

Galaxy Evolution, quasars, the circumgalactic medium, the intergalactic medium

Timothy D. Johnson

Bayesian methoda and statistical modeling of biomedical data

Vicki Johnson-Lawrence

Epidemiologic methods in chronic disease risk
Dani Jones

Dani Jones

Gaussian processes, Great Lakes, adjoint modeling, data assimilation, oceanography, unsupervised classification

David Jurgens

computational social science and natural language processing
Niko Kaciroti

Niko Kaciroti

Bayesian Modeling, dynamic models.

Catherine Kaczorowski

Alzheimer's, cognitive aging, computational neuroscience, learning and memory, multi-model analyses, neurodegeneration, resilience, systems genetics