Michael Wagner, PhD

Faculty Liaison, Biomedical Informatics Core

Associate Professor, UC Department of Pediatrics

Phone: 513-636-2935


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Large-scale optimization; applications in bioinformatics

Visit the Wagner Lab.


Michael Wagner, PhD, works on applications of machine learning techniques to bioinformatics problems such as protein structure prediction, disease classification and protein identification. His research lab currently is investigating machine-learning based scoring algorithms for peptide mass fingerprinting to better understand how to optimally mine mass spectrometry data to make high-confidence predictions of protein identities. The underlying computational engine for many of these problems is a massively parallel implementation of a linear programming solver (PCx), which can solve large-scale support vector regression, support vector machine and linear feasibility problems. 

Dr. Wagner also is involved in collaborations to perform genome-wide association studies, where his work has concentrated on developing an adequate, rapid data flow infrastructure that includes parallelized genotype calling algorithms.

Education and Training

Dipl. Wi-Ing.: Universitaet Karlsruhe, Germany, 1995.

MS: Operations Research, Cornell University, Ithaca, New York, 1998.

PhD: Operations Research, Cornell University, Ithaca, New York, 2000.


View PubMed Publications