Data science is inherantly multi-disciplinary. Thus, researchers and educators of data science can be found in a wide area of disciplines. The MSU community members listed below are involved in various aspects of data science research and education in application areas such as molecular, biological and biomedical data, the evolution of our galaxies, sports analytics, recommender systems, cybersecurity, and the societal and ethical impacts of a data-driven world.

People

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Jason Clark

Professor
Head, Special Collections and Archival Informatics
MSU Library

Clark writes and presents on a broad range of topics including semantic web development, digital library development, metadata and data modeling, web services and APIs, search engine optimization, and interface design.

   Renne Library
   (406) 994-6801
   jaclark@montana.edu
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Bree Cummins

Assistant Professor
Department of Mathematical Sciences

Dr. Cummins works with molecular biology data, including RNAseq and flow cytometry data, both single time point and time series, in order to infer genetic networks inside the cells of an organism and to assess the performance and diagnose problems in engineered genetic circuits. The techniques she uses could also be applied to other types of data, including proteomics and metabolomics. 

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Brittany Fasy

Associate Professor
Gianforte School of Computing and
Department of Mathematical Sciences

Dr. Fasy is a researcher in topological data analysis. She co-leads the CompTaG research group, started in Fall 2015. She is interested in increasing diversity in math and CS, as evidenced through serving on the steering committee for women in computational topology and principal investigator on the MSU Storytelling Project.

   Barnard Hall 363
   (406) 994-4804
   brittany.fasy@montana.edu
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Tomas Gedeon

Professor of Mathematics
Department of Mathematical Sciences

Dr. Gedeon is a mathematical biologist, who uses many different approaches to understand complex biological systems as gene regulatory networks, microbial consortia and cell regulation. His focus is on developing models of dynamics of these systems, often using data analysis to extract relevant information from experiments to validate and inform the models. 

   Wilson Hall 2-232
   (406) 994-5359
   tgedeon@montana.edu
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Mark Greenwood

Professor of Statistics
Department of Mathematical Sciences

Dr. Greenwood's research interests include high dimensional data analysis and visualization (especially related to functional data analysis), longitudinal data analysis and hierarchical modeling, measurement error correction methods, philosophy of statistics, and model selection techniques. 

   Wilson Hall 2-228
   (406) 994-1962
   greenwood@montana.edu
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Stacey Hancock

Associate Professor of Statistics
Department of Mathematical Sciences

Dr. Hancock is a researcher in statistics and data science education. She is also a PI on an NSF grant to bringcomputer science to rural and American Indian middle school students in Montana through storytelling: MSU Storytelling Group.

   Wilson Hall 2-195
   (406) 994-5350
   stacey.hancock@montana.edu 
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Andrew Hoegh

Associate Professor of Statistics
Department of Mathematical Sciences

Dr. Hoegh is an applied Bayesian statistician, and much of his work is motivated by working on problems with scientists. The general focus of his research is Bayesian computation for data analyses with complicated structure, including spatial and spatiotemporal components, with applications in the environmental or ecological sciences and sports analytics.

   Wilson Hall 2-241
   (406) 994-5340
   andrew.hoegh@montana.edu
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Sara Mannheimer

Associate Professor
Data Librarian
MSU Library

Mannheimer's research is rooted in the examination of the social, ethical, and technical issues that arise in a data-driven world. She has published work about data privacy, social media data curation, and digital preservation.

   Renne Library 234
   (406) 994-3361
   sara.mannheimer@montana.edu
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Brendan Mumey

Professor
Gianforte School of Computing

Dr. Mumey is a researcher in algorithms, optimization, networking, and computational biology.

   Barnard Hall 364
   (406) 994-7811
   brendan.mumey@montana.edu
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Christine (Eunyoung) Sung

Associate Professor of Marketing
Jake Jabs College of Business and Entrepreneurship

Dr. Sung is a researcher in consumer data mining, applied technology (AR/VR) marketing, international business/retailing strategies, and PLS-SEM (partial least squares - structural equation modeling).

   Jabs Hall 236
   (406) 994-6187
   christinesung@montana.edu
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David Nidever

Assistant Professor
Department of Physics

Dr. Nidever's research focuses on understanding the structure, formation and evolution of our galaxy and its largest satellite galaxies, the Magellanic Clouds, using several large surveys. He also works for the NOAO Data Lab.

   Barnard Hall 202
   (406) 994-7037
   david.nidever@montana.edu
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John Sheppard

Professor
Gianforte School of Computing

Dr. Sheppard is a researcher in probabilistic graphical models, machine learning, deep learning, evolutionary algorithms, swarm-based algorithms, fault diagnostics, fault prognostics, health management, distributed optimization, and data mining.

   Barnard Hall 365
   (406) 994-4835
   john.sheppard@montana.edu
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Andreas Thorsen

Associate Professor of Management

Jake Jabs College of Business and Entrepreneurship

Dr. Thorsen is an operations researcher whose research interest is the application of optimization to supply chains and health services.

   Jabs Hall 230
   (406) 994-6196
   andreas.thorsen@montana.edu
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Bradley Whitaker

Assistant Professor
Department of Electrical and Computer Engineering

Dr. Whitaker is a researcher in applied machine learning. He focuses on modifying traditional ML algorithms to more effectively deal with constraints present in many real-world datasets, such as class imbalance and incomplete/missing input data.

   Cobleigh Hall 630
   (406) 994-6942
   bradley.whitaker1@montana.edu
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Dominique Zosso

Associate Professor of Mathematics
Department of Mathematical Sciences

Dr. Zosso's research interests are variational and PDE methods, and efficient algorithms to solve inverse problems in imaging, computer vision, and related machine learning applications. His research explores the commonalities between problems and methods in imaging on the one side, and data science and machine learning on the other side.

   Wilson Hall 2-223
   (406) 994-5354
   dominique.zosso@montana.edu

 

If you are an MSU researcher in data science and would like to be listed on this page, please email Stacey Hancock at stacey.hancock@montana.edu.