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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Albert Shih

Custom devices to improve the quality of care

Yuki Shiraito

Bayesian statistical models and large-scale computational algorithms for political science

Ginger Shultz

Analysis of course placement, skills transfer and scientific reasoning

Yajuan Si

Bayesian, confidentiality protection, missing data, statistics, survey

Kathleen Sienko

Automating and Personalizing Home-Based Balance Training
John Silberholz

John Silberholz

clinical trial data
Mehrdad Simkani

Mehrdad Simkani

Rational approximation in the complex domain

Michael Sjoding

healthcare, machine learning
Katie Skinner

Katie Skinner

Robot vision and perception, field robotics

Stephen Smith

Using large data to examine rates and modes of evolution

Katie Snyder

Ethics and communication in community-engaged design
Peter Song

Peter Song

Data Integration, distributed inference, machine learning

Zheng Song

Edge Computing, Federated Learning, Web Services
S. Sriram

S. Sriram

Brand and product portfolio management
Siddhartha Srivastava

Siddhartha Srivastava

Scientific Learning for Applied Mechanics

Kevin Stange

Education policy, Higher education, Labor economics