Around 260 U-M faculty members from over 60 departments are affiliated with the Michigan Institute for Data Science, providing them access to collaboration opportunities, support for research funding submissions, and updates on data science news and events at U-M and beyond.

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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Vicki Johnson-Lawrence

Epidemiologic methods in chronic disease risk

Matthew Johnson-Roberson

Visualization and interpretation of massive data to monitor the Earth

Jack D. Kalbfleisch

Analyzing failure time or event history data

Hyun Min Kang

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

Steven J. Katz

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

Matthew Kay

Communicating uncertainty, and personal informatics, usable statistics

Branko Kerkez

Smart and adaptive water systems

Marouane Kessentini

Search-based software engineering and software refactoring

James Kibbie

Analysis of Bach's organ music and performance

John Kieffer

Simulation-based predictive design for new materials

Jinseok Kim

Text disambiguation in scholarly data

Aaron A. King

Statistical inference for mechanistic models of infectious disease

Antonios M. Koumpias

Behavioral tax compliance and health economics

Danai Koutra

Mining and making sense of interconnected or graph data

Anna Kratz

Characteristics and mechanisms of chronic clinical conditions

Aradhna Krishna

Sensory marketing