Vermont Complex Systems Center Research Groups

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Group Leads: Chris Danforth and Peter Dodds

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

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 and Mads Almassalkhi

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 and Jean-Gabriel Young
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

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

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.

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Group Lead: Brian Tivnan

The Computational Finance Lab is a joint venture of the University of Vermont and The MITRE Corporation. Its purpose is to study modern financial markets from a systems perspective using the tools of statistical physics, systems engineering, and data science. Its major research foci are empirical market microstructure and agent-based modeling of financial markets.

The University of Vermont (UVM) Spatial Analysis Laboratory (SAL) is a research facility located within the Rubenstein School of the Environment and Natural Resources. The SAL brings together faculty, staff, and students from across campus who share a passion for using geospatial technology to solve pressing challenges in the natural, physical, and social sciences. In partnership with the USDA Forest Service, the SAL has carried out tree canopy assessments for over 80 communities throughout North America, giving decision-makers data analytics that helps them to chart a greener future. The SAL is also home to UVM’s Unmanned Aircraft Systems (UAS) Team, which uses drone technology in areas ranging from disaster response to invasive species mapping.

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Computational Ethics Lab
Group Leads: Randall Harp and Peter S. Dodds

The University of Vermont (UVM) Computational Ethics Lab is a research group located in the Vermont Complex Systems Center. Our team brings together a post-disciplinary group of researchers, faculty, and students working in complex systems, data science, mathematics, computer science, and philosophy. This research group works to gain a deeper understanding of the ethical impacts of modern socio-technological systems. Research areas include: multi-level data ethics, privacy, distributed consent, and network structure and dynamics of data flow.

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Group Leads: James Bagrow and Laurent Hébert-Dufresne

The goal of the UVM project is to deepen understanding of how people, teams and organizations thrive in technology-rich settings, especially in open-source projects and communities. The Google award will establish a collaboration between the Google Open Source team and UVM to begin building a community-oriented body of research focused on understanding how open source platforms are used and what makes technology-rich environments thrive.

The MassMutual Center of Excellence for Complex Systems and Data Science will initiate research projects and programs aimed at better understanding human wellness through data analytics, as well as programming to cultivate a strong pipeline of data science talent.