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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Ming Xu

Computational and data-enabled methodology for sustainability

Jieping Ye

Computational methods for biomedical data analysis and informatics

Amy M. Yorke

Physical therapy education

Jon Zelner

Spatial analysis, social network analysis and dynamic modeling for infectious diseases

Jun Zhang

Algebraic and geometric methods for data analysis

Xiang Zhou

Statistical and computational methods for genetic and genomic studies

Ji Zhu

machine learning, network analysis and high-dimensional data analysis for health sciences

Qiang Zhu

Techniques supporting queries on large datasets in non-ordered discrete data space

Paul Zimmerman

Computational chemical reaction discovery

Sebastian Zoellner

Methods and applications in statistical genetics