https://www.uvm.edu/cems
Overview
The College of Engineering and Mathematical Sciences provides an educational program in Complex Systems and Data Science (CSDS) that includes education offerings at three levels:
- A 5-course Graduate Certificate in Complex Systems that may be taken by any graduate student at UVM to augment their degree.
- An M.S. in CSDS which is a 2-year degree with optional disciplinary tracks, and which UVM undergraduates may initiate through an Accelerated Master's Program.
- A Ph.D. in CSDS which will allow students to fully develop a deep portfolio of published research, thereby opening the door to high level research positions in, for example, government, industry, or academia.
The educational program naturally complements UVM’s undergraduate degree in Data Science but also thematically connects with many fields across the university.
The program's overall goal is to help students become protean data scientists with eminently transferable skills. Students are provided with a broad training in computational and theoretical techniques for (1) describing and understanding complex natural and sociotechnical systems, enabling them to then, as possible, (2) predict, control, manage, and create such systems. Students will be trained in: Industry standard methods of data acquisition, storage, manipulation, and curation; visualization techniques, with a focus on building high quality web-based applications; finding complex patterns and correlations through, for example, machine learning and data mining; powerful ways of hypothesizing, searching for, and extracting explanatory, mechanistic stories underlying complex systems—not just how to use black box techniques; combining the formulation of mechanistic models (e.g., toy physics models) with genetic programming.
Degrees
Complex Systems and Data Science AMP
Complex Systems and Data Science CGS
Complex Systems and Data Science M.S.
Complex Systems and Data Science Ph.D.
Allgaier, Nicholas; Assistant Professor, Department of Psychiatry; Ph.D., University of Vermont
Bagrow, James; Associate Professor, Department of Mathematics and Statistics; PHD, Clarkson University
Bongard, Joshua C.; Professor, Department of Computer Science; PHD, University of Zurich
Cheney, Nicholas A.; Assistant Professor, Department of Computer Science; PHD, Cornell University
Danforth, Chris; Professor, Department of Mathematics and Statistics; PHD, University of Maryland College Park
Dodds, Peter Sheridan; Professor, Department of Computer Science; PHD, Massachusetts Institute of Technology
Galford, Gillian Laura; Research Associate Professor, Rubenstein School of Environment and Natural Resources; PHD, Brown University
Garavan, Hugh P.; Professor, Department of Psychiatry; PHD, Bowling Green State University
Harp, Randall; Associate Professor, Department of Philosophy; PHD, Stanford University
Hébert-Dufresne, Laurent; Associate Professor, Department of Computer Science; PHD, Université Laval, Québec, Canada
Lovato, Juniper; Research Assistant Professor, Department of Computer Science; PhD, University of Vermont
Niles, Meredith; Associate Professor, Department of Nutrition and Food Sciences; PHD, University of California-Davis
Patania, Alice; Assistant Professor, Department of Mathematics and Statistics; PHD, Politecnico di Torino
Pespeni, Melissa H.; Assistant Professor, Department of Biology; PHD, Stanford University
Price, Matthew; Associate Professor, Department of Psychological Science; PHD, Georgia State University
Ricketts, Taylor H.; Professor, Rubenstein School of Environment and Natural Resources; PHD, Stanford University
Rizzo, Donna Marie; Professor, Department of Civil and Environmental Engineering; PHD, University of Vermont
Wshah, Safwan; Associate Professor, Department of Computer Science; PHD, State University of New York at Buffalo
Young, Jean-Gabriel; Assistant Professor, Department of Computer Science, PHD, Université Laval