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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Jie Liu

Machine learning and computational genomics

Liu Liu

utilizing computational methods to gain insights into molecular mechanisms of heart regeneration
Mingyan Liu

Mingyan Liu

Stochastic control, game theory and mechanism design, optimization

Zhixin (Jason) Liu

capacity allocation, pricing, scheduling

Zhongming Liu

computational and cognitive neuroscience, deep neural networks
Sabine Loos

Sabine Loos

Data and user-driven approaches on disasters and equity
Hernán López-Fernández

Hernán López-Fernández

Macroevolution and patterns of diversity in freshwater fishes

Vahid Lotfi

Improving efficiency and utilization of outpatient clinics

Jin Lu

Bioinformatics, Health-informatics, PAC learning, machine learning, optimization

Wei Lu

integrating human knowledge into machine learning
Gary Luker

Gary Luker

Quantitative imaging, cancer biology

Kathryn Luker

Molecular imaging of single cell signaling in cancer
Di Ma

Di Ma

Security, and applied cryptography, privacy

Lin Ma

ML/AI techniques to automate database administration

Maggie Makar

Artificial Intelligence, causality, healthcare, machine learning
Puneet Manchanda

Puneet Manchanda

Using econometrics and machine learning methods to infer causality