Vermont Complex Systems Center Research Groups

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Group Leads: Chris Danforth and Peter Dodds
Group Members: Eric Clark, Tyler Gray, David Dewhurst, Aaron Schwartz, Ben Emery, John Ring, Michael Arnold, Yu Jiang, Sven McCall, Laura Jennings, Henry Mitchell
Danforth is the Flint Professor of Mathematical, Natural, and Technical Sciences at the University of Vermont. He co-directs the Computational Story Lab, a group of applied mathematicians at the undergraduate, masters, phd, and postdoctoral level working on large-scale, system problems in many fields including sociology, nonlinear dynamics, networks, ecology, and physics.
Danforth’s background is in the application of Chaos Theory to weather & climate prediction. His current work is in Computational Social Science, exploring human behavior through social media data. Danforth is the co-inventor of, a socio-technical instrument measuring daily happiness based on 100 billion Twitter messages. He has also developed algorithms to identify predictors of depression from Instagram photos.

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Group Lead: Josh Bongard
Group Members: Roman Popov, Anton Bernatskiy, Collin Cappelle, Sam Kriegman, Joshua Powers, Alex Ram, Jack Felag

Can we automatically design increasingly smart robots that will help humans and work alongside them? To do so, we draw on ideas from evolution, crowdsourcing, and neuroscience.

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Group Lead: Paul Hines
Group Members: Molly Molly Rose Kelly-Gorham, OlaOluwa Akinola, Andrew Klem, Austin Thomas, Bernard Achinda
The mission of the energy and complexity group is to understand the complexity of electricity and to use that understanding to make energy systems work better (cleaner, more reliable and less costly) through innovative research. Our group works in close collaboration with the Vermont Complex Systems Center, the UVM Smart Grid IGERT program, and the eEnergy Vermont Smart Grid project.

Group Lead: Laurent Hébert-Dufresne
Group Members: Guillaume St-Onge, Brendan Case, Blake Williams, Alexander Daniels, Samuel Rosenblatt
Our research deals with the interaction and coevolution of structure and dynamics. Our focus is on network theory, but also general nonlinear dynamics in structured systems. Examples include social networks interacting with the spread of diseases and ideas, the shape of forests coevolving with forest fires, and the structure of metabolic networks influencing interactions in microbial communities.

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Group Lead: James Bagrow
Group Members: Andrew Becker, Daniel Berenberg, Jeremy Holden, Abigail Hotaling, Ryan Grindle, Brian Colombini, William Cuoco, Beau Duval, Olivea Hurd
We are researchers using mathematical modeling, computational methods, and big data to understand and predict the behavior of complex social and technological systems, from team collaborations and activity on social media to power grids, the stock market, and

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Group Lead: Nick Cheney
Group Members: Shawn Beaulieu, Ollin Langle, Lapo Frati
The UVM Neurobotics Lab draws inspiration from natural systems in biology, psychology, and neuroscience to help us design artificial neural networks, autonomous robots, and decision making systems. We also apply these machine learning systems to help provide solutions and insights towards complex systems in our society — including social, environmental, and biomedical domains.