Around 260 U-M faculty members from over 60 departments are affiliated with the Michigan Institute for Data Science, providing them access to collaboration opportunities, support for research funding submissions, and updates on data science news and events at U-M and beyond.

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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Aaron A. King

Statistical inference for mechanistic models of infectious disease

Antonios M. Koumpias

Behavioral tax compliance and health economics

Danai Koutra

Mining and making sense of interconnected or graph data

Anna Kratz

Characteristics and mechanisms of chronic clinical conditions

Aradhna Krishna

Sensory marketing

Jeffrey C. Lagarias

Number theory, dynamical systems, optimization

Carl Lagoze

Interoperability in information systems

Walter S. Lasecki

Continuous real-time crowdsourcing and the ‘crowd agent’ model

Ho-Joon Lee

Algorithms and models for multi-dimensional large-scale data

Jon Lee

Nonlinear discrete optimization

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