Around 260 U-M faculty members from over 60 departments are affiliated with MIDAS.

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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Honglak Lee

Machine learning and its applications to artificial intelligence

Peter Lenk

Bayesian methods and data mining

Margaret C. Levenstein

Computational social science

Elizaveta Levina

Statistical inference on realistic models for network

Jun Li

Empirical operations management and business analytics

Jun Li

Genetic and genomic analyses of complex phenotypes

Weiqi Li

New method to solve the traveling salesman problem

Yi Li

Statistical methods for kidney epidemiology

Roderick Little

The analysis of data sets with missing values

Mingyan Liu

Stochastic control, game theory and mechanism design, optimization

Xuefeng (Chris) Liu

Statistical models for critical issues

Jie Liu

Machine learning and computational genomics

Henry Liu

Traffic network monitoring, modeling and control

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