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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Thomas A. Schwarz

Thomas A. Schwarz

Experimental particle physics utilizing advanced AI and Machine Learning

Clayton Scott

Quantitative predictions and inferences about large, complex data

Nicole Seiberlich

MRI, Magnetic Resonance Imaging, cardiac MRI, precision medicine, quantitative MRI, radiology workflow

Lawrence Seiford

Quality engineering, productivity analysis and process improvement
Ananda Sen

Ananda Sen

Competing risks, and inter-rater agreement, recurrent event data
srijan sen

Srijan Sen

Gene-environment interaction and their effect on stress, anxiety and depression

Yulia Sevryugina

COVID-19 literature, Information dissemination, Pandemic publishing, Publishing landscape

Matthew Shapiro

Improving the quality of national economic statistics

Atiyya Shaw

data and methods that prioritize user-centered outcomes in urban systems

Kerby Shedden

Applied statistics, data science and computing with data
Jie Shen

Jie Shen

Digital diagnosis of material damage based on large-scale data

Liyue Shen

biomedical AI development

Siqian Shen

Optimization and risk analysis of energy, cloud-computing and transportation, healthcare

David H. Sherman

Biosynthetic Gene Cluster Mining, Genome Sequence Analysis, Virtual Structure Elucidation, drug discovery, natural products

Cong Shi

Data-driven optimization for operations management

Xu Shi

EHR data, causal inference