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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Alfred Hero

Theory and algorithms for data collection, analysis and visualization

Todd I Herrenkohl

child and family well-being; psychosocial research in health-risk behaviors in youth and adults

Joseph Himle

Monitoring and treatment of trichotillomania

James R. Hines Jr.

Donation behavior and wealth transfer
Jana Hirschtick

Jana Hirschtick

social epidemiology

Todd Hollon

machine learning for medical imaging
Jingwen Hu

Jingwen Hu

Reducing the incidence of injuries and fatalities in traffic accidents

Tung-Hui Hu

Media scholar interested in the material and historical dimensions of data science.
Wei Hu

Wei Hu

Deep Learning, Representation Learning, machine learning, optimization, theory

Zhen Hu

Additive Manufacturing, Bayesian methods, Big data analytics, Material, Reliability, Uncertainty quantification, machine learning, optimization

Xun Huan

Uncertainty quantification, and numerical optimization, data-driven modeling

Xianglei Huang

climate diagnostics, data modeling, optimization, remote sensing, time-series analysis

Jane E. Huggins

EEG-based brain-computer interfaces

Muzammil M. Hussain

Global communication and comparative politics
Uduak Inyang-Udoh

Uduak Inyang-Udoh

Control theory, Graph theory, Physics-guided machine learning, energy systems, manufacturing

Edward Ionides

Time series analysis for ecology, epidemiology, health economics and biology