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Laurent Hébert-Dufresne
CNWW Director

Assistant Professor, University of Vermont Department of Computer Science; Member, The Vermont Complex Systems Center

Laurent studies the interaction of structure and dynamics. His research involves network theory, statistical physics and nonlinear dynamics along with their applications in epidemiology, ecology, biology, and sociology. Recent projects include comparing complex networks of different nature, the coevolution of human behavior and infectious diseases, understanding the role of forest shape in determining stability of tropical forests, as well as the impact of echo chambers in political discussions.

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Antoine Allard
CNWW Director

Assistant professor, Département de physique, de génie physique et d'optique, Université Laval, Québec, Canada

Antoine's research combines statistical mechanics, graph theory, nonlinear dynamics and geometry to develop mathematical models of complex networks and to study the structure/function relationship specific to complex systems. His recent projects involve the mapping of real complex networks unto hyperbolic space to characterize the evolution of international trade, the use of greedy routing to unveil the spatial organization of the brain at various scales and across species, and the analytical solution of percolation on networks with a strong induced core-periphery structure to assess the potential of the Zika virus as a sexually transmitted infection.
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Jean-Gabriel Young
CNWW Co-Director

Assistant professor, Department of Computer Science, University of Vermont

I am a Research Assistant Professor at the Department of Computer Science of The University of Vermont, VT, USA. I also hold an appointment at the Vermont Complex Systems Center. My research is at the intersection of statistical inference and complex systems.

Previously, I was a James S. McDonnell Foundation Fellow at the Center for the Study of Complex Systems of the University of Michigan, where I was mentored by Prof. Mark Newman. I obtained my PhD in Physics from Université Laval, under the guidance of Prof. Louis J. Dubé and Prof. Patrick Desrosiers.

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Brooke Foucault Welles- Professor, Communication Studies in the College of Arts, Media and Design, Northeastern University Network Science Institute

Brooke Welles is a Professor of Communication Studies in the College of Arts, Media and Design. Her research examines how social networks shape behavior, including how individuals identify resources within their social networks and leverage them to achieve personal and organizational goals.

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Peter Dodds
Director, Vermont Complex Systems Center

Dodds's research focuses on system-level, big data problems in many areas including language and stories, sociotechnical systems, Earth sciences, biology, and ecology. His foundational funding was an NSF CAREER award granted to study sociotechnical phenomena (2009-2015). Together with Chris Danforth, he co-runs the Computational Story Lab.

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C. Brandon Ogbunu
Assistant Professor of Ecology and Evolutionary Biology
Yale University

C. Brandon Ogbunu is an Assistant Professor in the Department of Ecology and Evolutionary Biology at Yale University. He is an evolutionary systems biologist, and uses experimental evolution, mathematical modeling, and computational biology to better understand the underlying causes and consequences of disease, across scales: from the biophysics of proteins involved in drug resistance to the social determinants underlying disease. In doing so, he aims to develop theory that enriches our understanding of the evolutionary and ecological underpinnings of disease, while contributing to practical solutions for clinical medicine and public health. Read more about his research and activities here:

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Elizabeth Hobson
Assistant Professor, Department of Biological Sciences, University of Cincinnati

I am a biologist who specializes in animal behavior, behavioral ecology, cognitive ecology, and social cognition. My research focuses on social information: what animals know about their social worlds, how they come to know it, and what they do with that information.

To address these questions, I integrate aspects of ecology and evolution to determine how the combination of sociality and cognition affect the emergence of group social structures from a combination of individual-level social actions, cognitive abilities, and decisions about future interactions. Combining this perspective into a feedback loop, and developing and applying new quantitative tools, allows me to back-infer what animals know about their social worlds by looking at how their decisions about social interactions are contingent on different kinds of social knowledge. Detecting the use of social knowledge provides new insight into the connections between social decisions and cognitive processing, how they can be affected by ecological dynamics, and how they can lead to the evolution of complex sociality.

Much of my previous research focused on avian sociality, where I investigated social behavior and network structures in parrots. In my current research I apply these tools to a much wider range of species, from ants to primates, and even humans, while incorporating more quantitative and computational approaches.

I am currently an Assistant Professor at the University of Cincinnati. My goal for research in my lab is to use rigorous comparative methods and an evolutionary perspective to discover ways in which the extreme sociality of some species emerged, through investigating what individuals understand about their social worlds and the strategies individuals use to balance the costs and benefits of social living.

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Daniel B. Larremore
Asst. Professor, Univ. Colorado Boulder
BioFrontiers Institute & Dept. of Computer Science

My research focuses on developing methods of networks, dynamical systems, and statistical inference, to solve problems in social and biological systems. I try to keep a tight loop between data and theory, and learn a lot from confronting models and algorithms with real problems.

I obtained my PhD in Applied Mathematics from the University of Colorado Boulder in 2012, advised by Juan G. Restrepo, after which I spent three years as a postdoctoral fellow at the Harvard T.H. Chan School of Public Health studying the genetic epidemiology of malaria in the Center for Communicable Disease Dynamics. I then joined the Santa Fe Institute as an Omidyar Fellow until 2017, when I joined the faculty at the University of Colorado Boulder in the Department of Computer Science and the BioFrontiers Institute.
Malaria's antigenic variation and evolution - The var genes of the malaria parasite P. falciparum evolve according to complicated and unknown rules, with selective pressures at multiple scales both within hosts and between hosts. I create and use mathematical tools to understand the structural and evolutionary constraints on var gene evolution, and their relationships with parasite virulence, population structure, and epidemiology.

Networks and theory - The processes that generate complex networks leave hints about themselves in the patterns of edges, and the relationships between those patterns and vertex metadata. I work on mathematical descriptions of graph ensembles, inference of community structures, vertex ordering or ranking, and using metadata to better understand network formation.
The scientific ecosystem - The scientific method of hypothesis, experiment, and conclusion poorly describes modern scientific discovery and productivity. Instead, science is done by people who play various social roles in the ecosystem of science. I investigate faculty hiring, productivity patterns, scientific careers, and the dynamics of discovery through large-scale data collection and modeling.

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Cassidy R Sugimoto, Professor of Informatics, Indiana University Bloomington

Cassidy Sugimoto is Professor of Informatics at the School of Informatics, Computing, and Engineering at Indiana University Bloomington. She is also currently serving a rotation with the National Science Foundation as the Program Director for the Science of Science and Innovation Policy (SciSIP) program. Sugimoto's research expertise is broadly situated in the domains of science policy, scholarly communication, and scientometrics. Simply speaking, she investigates the ways in which knowledge is produced, disseminated, and rewarded, with a particular interest in issues of diversity and inclusion.

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Samuel Scarpino
Assistant Professor in the Network Science Institute at Northeastern University.

I am an Assistant Professor of Marine & Environmental Sciences and Physics and a core faculty member in the Network Science Institute at Northeastern University. I am also the Chief Data Scientist at My research spans a broad range of topics in complex systems and network science, including: infectious diseases, forecasting and predictive modeling, disease genomics and transcriptomics, outbreak surveillance, network science, and decision making under uncertainty. Our group, the Emergent Epidemics Lab, approaches these topics by investigating questions at the intersection of biology, behavior, and disease.

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Patrick Desrosiers - Affiliate Professor, Laval University , Centre de recherche CERVO; Département de physique, Université Laval; Dynamica research group

Theoretical and mathematical physicist Fields of interest: classical and quantum integrable systems, symmetric functions, random matrix theory, orthogonal polynomials in many variables, representation theory, conformal field theory, supersymmetry, complex systems.

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Dominique Gravel - Professor, Holder of the Canada Research Chair in Integrative Ecology, Université de Sherbrooke

Research Themes:
Spatial ecology, biogeography and ecology of metacommunities; Networks of ecological interactions; Theoretical, numerical and computational ecology; Biodiversity and ecosystem functioning; Climate change and forestry.

Current Research:
Ecosystems are difficult to study because of the diversity of interactions between species and their complex relationships with the environment. If understanding the distribution of biodiversity is already a challenge, predicting its response to global change is even more so. I adopt a research approach that integrates several disciplines of ecology to better understand the impact of global changes on biodiversity. Thus, I use notions of biogeography, community ecology and ecosystem functioning.

My research program ultimately aims to develop a global model of ecosystem functioning. To do this, I propose new conceptual tools and implement them using mathematical and computer models, as well as massive data ( Big Data ). I also carry out laboratory experiments using a microbial ecosystem (the food web inhabiting the leaves of carnivorous plants). My research will produce biodiversity scenarios for the future. This knowledge is needed to protect biodiversity in a changing environment.

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Jim Bagrow
Assistant Professor, University of Vermont
Department of Mathematics and Statistics

Bagrow's interests include: Complex Networks (community detection, social modeling and human dynamics, statistical phenomena, graph similarity and isomorphism), Statistical Physics (non-equilibrium methods, phase transitions, percolation, interacting particle systems, spin glasses), and Optimization(glassy techniques such as simulated/quantum annealing, (non-gradient) minimization of noisy objective functions).

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Hyejin Youn - Assistant Professor at Kellogg School of Management at Northwestern University, and Northwestern Institute on Complex Systems (NICO)

I am an assistant professor at Kellogg School of Management at Northwestern University, and Northwestern Institute on Complex Systems (NICO). I was a research fellow at Santa Fe Institute and Harvard Kennedy School, and visiting scientist at MIT Media Lab. Before that, I was a senior research fellow at Mathematical Institute at University of Oxford , and Institute for New Economic Thinking at the Oxford Martin School; and ran a National Science Foundation grant (USA) to study Technological Change from the Map of Capabilities with Aaron Cluaset, the University of Colorado at Boulder. My PhD is in Statistical Physics at KAIST. I serve on the editorial board of PLOS One.

My research aims to develop a mathematical and computational framework to understand complex systems. These include (see the detail here):
Science of Cities
Pathway of Innovation
Linguistics (Semantic shift)

Please visit my publication page or Google scholar profile for the more details on my publications

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Eleanor Power - Assistant Professor, Department of Methodology, London School of Economics

Eleanor Power is an Assistant Professor in the Department of Methodology. She completed her PhD in Anthropology at Stanford University in 2015. Prior to joining LSE in 2017, she was an Omidyar Postdoctoral Fellow at the Santa Fe Institute.

Research interests
Eleanor is an anthropologist interested in how religious belief, practice, and identity interact with and shape interpersonal relationships.

She studies these dynamics through fieldwork conducted in the South Indian state of Tamil Nadu, using a combination of qualitative and quantitative methods, primary among which is social network analysis. Her work is informed by signaling theory and the wider scholarship of human behavioral ecology. She is interested in the dynamics of social networks, especially relative to the factors that influence cooperation, competition, trust, and prestige. More generally, Eleanor is interested in investigating questions regarding: the role of religion in society, the interaction between costly signaling and cooperation, gender differences in prominence and social capital, and the dynamics of gossip and social censure.