Affiliated Faculty

The MIDAS affiliate faculty community consists of over 450 U-M faculty members from over 60 departments.


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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Stefanus Jasin

approximation algorithm, business analytics, machine learning, optimization

Judy Jin

Data fusion for improving system operation and quality

Timothy D. Johnson

Bayesian methoda and statistical modeling of biomedical data

Vicki Johnson-Lawrence

Epidemiologic methods in chronic disease risk

Matthew Johnson-Roberson

Visualization and interpretation of massive data to monitor the Earth

David Jurgens

computational social science and natural language processing

Niko Kaciroti

Bayesian Modeling

Jack D. Kalbfleisch

Analyzing failure time or event history data

Hyun Min Kang

Practical, accurate, and efficient methods for big data genome science

Jian Kang

Bayesian methods, composite likelihood approach and missing data problems, efficient statistical computation algorithms, graphical models, latent source separation methods, network inference, ultrahigh-dimensional feature selection

Trishul Kapoor

ICU Vital Sign for Opioid Use Prediction

Steven J. Katz

Cancer treatment communication, and quality of care, decision-making

Daniel P. Keating

Longitudinal analyses across multiple databases, population modeling.

Evan Keller

Single cell and spatiotemporal analyses of healthy and diseased tissues

Branko Kerkez

Smart and adaptive water systems