Michael Cummings
Michael Cummings
Professor, UMIACS
Director, Data Science and Analytics M.S. Program
Director, Bioinformatics and Computational Biology M.S. Program
Teaching
- BSCI 471: Molecular Evolution
- BISI 620: Bioinformatics and Genomics
- BIOL 671: Molecular Evolution
- DATA 698: Research Methods and Study Design
- DATA 699: Capstone Research Project
Graduate Program Affiliations
- Bioinformatics & Computational Biology (BIOI)
- Biological Sciences (BISI): Behavior, Ecology, Evolution, and Systematics (BEES)
- Biological Sciences (BISI): Computational Biology, Bioinformatics, and Genomics (CBBG)
- Data Science (DATA)
Research Interests
Our research involves bioinformatics and computational biology with a particular focus on data analysis that spans a broad range of biomedical problems. We takes a broadly data science approach to research with objectives including description, hypothesis generation, hypothesis testing, prediction, and use machine learning, statistical and other methods.
Education
- Ph.D., Harvard University, 1992. Molecular evolution, bioinformatics, computational biology.
All Publications
BISI Concentration Areas
Behavior, Ecology, Evolution, and SystematicsComputational Biology, Bioinformatics, and Genomics
Latest Papers
Applying Wearable Sensors and Machine Learning to the Diagnostic Challenge of Distinguishing Parkinson’s Disease from Other Forms of Parkinsonism
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Biomedicines
Author(s): Rana M. Khalil, Lisa M. Shulman, Ann L. Gruber-Baldini, et. al
UMD Author(s): Michael Cummings
Machine Learning and Statistical Analyses of Sensor Data Reveal Variability Between Repeated Trials in Parkinson’s Disease Mobility Assessments
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Sensors
Author(s): Rana M. Khalil, Lisa M. Shulman, Ann L. Gruber-Baldini, et. al
UMD Author(s): Michael Cummings
Plasmodium vivax antigen candidate prediction improves with the addition of Plasmodium falciparum data
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npj Systems Biology and Applications
Author(s): Renee Ti Chou, Amed Ouattara, Shannon Takala-Harrison, et. al
UMD Author(s): Michael Cummings
Simplification of Mobility Tests and Data Processing to Increase Applicability of Wearable Sensors as Diagnostic Tools for Parkinson’s Disease
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Sensors
Author(s): Rana M. Khalil, Lisa M. Shulman, Ann L. Gruber-Baldini, et. al
UMD Author(s): Michael Cummings
Positive-unlabeled learning identifies vaccine candidate antigens in the malaria parasite Plasmodium falciparum
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npj Systems Biology and Applications
Author(s): Renee Ti Chou, Amed Ouattara, Matthew Adams, et. al
UMD Author(s): Michael Cummings
Engineered peptide-drug conjugate provides sustained protection of retinal ganglion cells with topical administration in rats
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Journal of Controlled Release
Author(s): Henry T. Hsueh, Renee Ti Chou, Usha Rai, et. al
UMD Author(s): Michael Cummings
Using Machine Learning to Understand the Relationships Between Audiometric Data, Speech Perception, Temporal Processing, And Cognition
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ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Author(s): Rana M. Khalil, Alexandra Papanicolaou, Renee Ti Chou, et. al
UMD Author(s): Michael Cummings
Machine learning-driven multifunctional peptide engineering for sustained ocular drug delivery
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Nature Communications
Author(s): Henry T. Hsueh, Renee Ti Chou, Usha Rai, et. al
UMD Author(s): Michael Cummings
A phylogenomic approach to resolving interrelationships of polyclad flatworms, with implications for life-history evolution
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Royal Society Open Science
UMD Author(s): Allen Collins, Michael Cummings
A critical assessment of gene catalogs for metagenomic analysis
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Bioinformatics
Author(s): Seth Commichaux, Nidhi Shah, Jay Ghurye, et. al
UMD Author(s): Michael Cummings, Mihai Pop
