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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Ivy F. Tso

Ivy F. Tso

Psychiatric disorders, brain network, computational and predictive models
Suleyman Uludag

Suleyman Uludag

Security, and optimization Smart Grid data, privacy

Thomas Valley

improving equity in ICU-care

Monica Valluri

Dynamical modeling and inference from stellar kinematics
Derek Van Berkel

Derek Van Berkel

Big Data, and machine learning for understanding land change at diverse scales, data science, spatial statistics

Mark P Van Oyen

Machine learning and optimization systems models for healthcare
Matthew VanEseltine

Matthew VanEseltine

Digging into data on science and academic careers

Ram Vasudevan

Optimization and Machine Learning to Improve Robotic Systems
Shravan Veerapaneni

Shravan Veerapaneni

Fast and scalable algorithms for differential and integral equations on complex moving geometries
Aditi Verma

Aditi Verma

Community-engaged design, Design research, complex systems, design tools
Angela Violi

Angela Violi

bacterial biofilms, microorganisms, nanochemistry, nanoparticles, sparsity, surrogate models
Venkat Viswanathan

Venkat Viswanathan

Scientific machine learning, differentiable physics

V. G. Vinod Vydiswaran

AI for evaluating trustworthiness in medical literature

Akbar Waljee

Use Data Science to promote high-value care in low resource settings.

Nils G. Walter

Intracellular single molecule, high-resolution localization
Lu Wang

Lu Wang

Natural language processing