- May 27, 2019DAY 1School and Satellites
- MAY 28, 2019DAY 2School and Satellites
- MAY 29, 2019DAY 3Main Conference
- MAY 30, 2019DAY 4Main Conference
- MAY 31, 2019DAY 5Main Conference
ABOUT NETSCI 2019
NetSci 2019 is the flagship conference of the Network Science Society, which aims to bring together leading researchers and practitioners working in the emerging research area of network science. The NetSci conference fosters multi-disciplinary communication and collaboration in network science research across computer and information sciences, physics, mathematics, statistics, the life sciences, neuroscience, environmental sciences, social sciences, finance and business, arts and design.
NetSci 2019 will be a combination of:
- An International School for students and non-experts
- Satellite Symposia
- A 3-day Conference featuring research in a wide range of topics and in different formats, including keynote and invited talks, oral presentations, posters, and lightning talks.
- * If you came to our site from www.netsci2019.net while using a mobile device you may want to visit our more mobile friendly domain
Dates - May 27 - 31, 2019
Location -Burlington, Vermont USA
Hosts - The Vermont Complex Systems Center
Hashtag - #Netsci2019
Location -Burlington, Vermont USA
Hosts - The Vermont Complex Systems Center
Hashtag - #Netsci2019
- Invited Speakers
Speaker List Coming Soon!
- Program Schedule
- Deadlines DeadlinesDeadline for submission of satellite proposals: December 11, 2018Deadline for abstract submission: January 10, 2019Deadline for Visualization Prize submission: February 20, 2019Early Registration Deadline - April 10, 2019Registration Deadline for Accepted Contributions - March 20, 2019Online Registration Deadline - May 20, 2019
- Organizers Conference Co-Chairs:Peter S. Dodds, Director of the Vermont Complex Systems Center, Professor, UVM Department of Mathematics and Statistics×
Peter's research focuses on system-level, big data problems in many areas including language and stories, sociotechnical systems, Earth sciences, biology, and ecology. Peter has created (and constantly evolves) a series of complex systems courses starting with Principles of Complex Systems. He co-runs the Computational Story Lab with Chris Danforth.
Laurent Hébert-Dufresne, Assistant Professor, UVM Department of Computer Science, 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.
At the Vermont Complex Systems Center, Juniper works across generations and geographical limits to make resources and knowledge on cutting-edge complexity science more accessible to those with a hunger and curiosity for learning and exploration. Juniper came to Burlington in 2018. She previously served as the Director of Education for the Santa Fe Institute, an independent complexity science research center. She is also a co-founder of MAKE Santa Fe, a not-for-profit community makerspace in Santa Fe, New Mexico. Juniper received her Master’s in the Western Classics from St. John’s College in 2013 where she completed a thesis on the nature of pleasure in work in Aristotle’s Nicomachean Ethics.
Program Committee Chair:Jim Bagrow, Assistant Professor, UVM Department of Mathematics and Statistics, The Vermont Complex Systems Center×
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).
Senior Program Committee:×
Our research is driven by an ongoing dialog between experimental measurements and theoretical modeling. We build our models on the most salient features of a system, and use our results as predictions and guidance for future experiments. Our diverse, interdisciplinary projects are characterized by the common goal of identifying organizing principles of complex systems.
Prof. Alex Arenas (Barcelona, 1969) got his PhD in Physics in 1996. In 1995, he got a tenure position at Dept. Computer Science and Mathematics (DEIM) at Universitat Rovira i Virgili, and in 1997 he became associate professor at the same department. In 2000, he was visiting scholar at the Lawrence Berkeley Lab. (LBL) in the Applied Mathematics group of Prof. Alexandre Chorin (University of California, Berkeley). After this visit, he started a collaboration with Berkeley, and in 2007 he became visiting researcher of LBL. Arenas has written more than 190 interdisciplinary publications in major peer reviewed including Nature, Nature Physics, PNAS, Physics Reports and Physical Review Letters, which have received more than 20000 citations. He is one of the few Europeans serving as Associate Editors of the most important publication in physics worldwide, the American Physical Society journal, Physical Review. He is in charge of the Complex Networks and Interdisciplinary Physics section of Physical Review E. He got the James Mc Donnell Foundation award for the study of complex systems in 2011. He was also recognized as ICREA Academia-Institució Catalana de Recerca i Estudis Avançats, a catalan award that promotes the most recognized scientists from Catalonia in 2011 and 2017. He serve as Editor in Journal of Complex Networks, and in Network Neuroscience. He was elected for the Steering Committee of the Complex Systems Society in 2012. He is external faculty of the Complexity Hub Science in Vienna from 2017. He is the leader of the research group ALEPHSYS.
My research interests are currently focused on the physics of networked multilevel complex systems. The comprehension of the interplay between the structure of the connectivity and the functionality of networked system is a major challenge for the physics of this era. Concepts that applied to the nowadays classical network theory, must be revisited in the framework of multilevel coupling scenarios, in what is being known as the physics of multilayer networks. The applicability of the understanding of the basic phenomena underlying these systems have direct applications in neuroscience, social sciences, systems biology and computer science. Specifically, I am particularly interested on the study of dynamic transitions in complex networks from a functional multilayer approach. It includes two complementary parts, building a complex networked framework for the analysis of activity signals and proposing physical models to validate the framework. I aim at creating a comprehensive mathematical formalism for constructing a functional time-varying multilayer network (whose layers are functional networks) from activity (eventually time-series) observations. Specific models, algorithms and/or tools will be developed to analyze the collective behavior of different models. Other fundamental aspect to develop concerns the acquisition and processing of data for the study of real systems. This it is an important issue given the strong interdisciplinary component that it implies, nowadays, to study complex networks trying to operate to the maximum of our experience in this field and trying to obtain the maximum possible scientific impact of our results.
Vittoria Colizza completed her undergraduate studies in Physics at the University of Rome Sapienza, Italy, in 2001 and received her PhD in Statistical and Biological Physics at the International School for Advanced Studies in Trieste, Italy, in 2004. She then spent 3 years at the Indiana University School of Informatics in Bloomington, IN, USA, first as a post-doc and then as a Visiting Assistant Professor. In 2007 she joined the ISI Foundation in Turin, Italy, where she started a new lab after being awarded a Starting Independent Career Grant in Life Sciences by the European Research Council Ideas Program (more info on the EpiFor project webpage). In 2011 Vittoria joined the Inserm (French National Institute for Health and Medical Research) in Paris where she now leads the EPIcx lab working on the characterization and modeling of the spread of emerging infectious diseases, by integrating methods of complex systems with statistical physics approaches, computational sciences, geographic information systems, and mathematical epidemiology. In 2017 she obtained the French academic degree HDR (Habilitation a Diriger des Recherches), and was promoted Director of Research at Inserm.
Tina Eliassi-Rad, Associate Professor, Network Science Institute, College of Computer and Information Science, Northeastern University×
Tina Eliassi-Rad is an Associate Professor of Computer Science at Northeastern University in Boston, MA. She is also on the faculty of Northeastern's Network Science Institute. Prior to joining Northeastern, Tina was an Associate Professor of Computer Science at Rutgers University; and before that she was a Member of Technical Staff and Principal Investigator at Lawrence Livermore National Laboratory. Tina earned her Ph.D. in Computer Sciences (with a minor in Mathematical Statistics) at the University of Wisconsin-Madison. Her research is rooted in data mining and machine learning; and spans theory, algorithms, and applications of massive data from networked representations of physical and social phenomena. Tina's work has been applied to personalized search on the World-Wide Web, statistical indices of large-scale scientific simulation data, fraud detection, mobile ad targeting, and cyber situational awareness. Her algorithms have been incorporated into systems used by the government and industry (e.g., IBM System G Graph Analytics) as well as open-source software (e.g., Stanford Network Analysis Project). In 2010, she received an Outstanding Mentor Award from the Office of Science at the US Department of Energy. For more details, visit http://eliassi.org.
James Gleeson holds a BSc in Mathematical Science and an MSc in Mathematical Physics from University College Dublin. In 1999 he completed his PhD in Applied Mathematics at Caltech. He has lectured at Arizona State University and at University College Cork, and since 2007 has held a Chair in Industrial and Applied Mathematics at the University of Limerick.
James’ research interests are in mathematical modelling of stochastic dynamics, with a particular focus on complex systems and networks. He is a SEES co-PI, has held three Principal Investigator awards from Science Foundation Ireland, and is a co-PI on a Future and Emerging Technologies project funded by the European Commission’s FP7. James is co-director of MACSI, the Mathematics Applications Consortium for Science and Industry (http://www.macsi.ul.ie/). MACSI researchers develop and apply mathematical techniques to assist collaborators from science and industry in solving real-world problems.
Neil Johnson’s research interests lie in the broad area of Complex Systems. He is a Fellow of the American Physical Society (APS) as well as the recipient of the 2018 Burton Award from the APS.
Neil heads up a new inter-disciplinary research group in Complexity at University of Miami (Physics Dept.) looking at collective behavior and emergent properties in a wide range of real-world Complex Systems: from the many-body effects involved in energy harvesting, information processing and coherence, through to cyberphysical systems and socioeconomic domains. The common feature which makes Complex Systems so hard to understand, and yet so fascinating to study, is that they all contain many interacting objects, with strong feedback from both inside and outside the system, and are typically far from equilibrium and exhibit extreme behaviors. Neil's research group is involved with interdisciplinary projects across multiple other departments and schools within the University of Miami, and other institutions both within U.S. and globally, e.g. Universidad de Los Andes in Bogota, Colombia.
Prior to coming to UM in 2007, Neil was Professor of Physics at Oxford University, having joined the faculty in 1992. He did his BA/MA at Cambridge University and his PhD at Harvard University as a Kennedy Scholar. He has published more than 200 research articles in international journals, and has published two books: "Financial Market Complexity" (Oxford University Press, 2003) and "Simply Complexity: A Clear Guide to Complexity Theory" (Oneworld Publishing, 2009). He also wrote and presented the Royal Institution Lectures in 1999 on BBC television, comprising five 1-hour lectures on “Arrows of Time”.
He is joint Series Editor for the book series "Complex Systems and Interdisciplinary Science" by World Scientific Press, and is the Physics Section Editor for the journal "Advances in Complex Systems". He is Associate Editor for "Journal of Economic Interaction and Coordination", and is an Editorial Board member of "Journal of Computational Science". He co-founded and co-directed CABDyN (Complex Agent-Based Dynamical Systems) which is Oxford University's interdisciplinary research center in Complexity Science, until leaving for Miami. He also co-directed Oxford University's interdisciplinary research center in financial complexity (OCCF).
Yu-Ru Lin, Associate Professor, School of Computing and Information, Joint appointment: Intelligent Systems Program (ISP), Political Science Department, University of Pittsburgh×
I am an associate professor at School of Computing and Information, University of Pittsburgh. I am interested in studying social and political networks, as well as computational and visualization methods for understanding network data. My work has focused on large-scale community dynamics, high-dimensional (rich-context) social information summarization and representation. I have been using massive social media data and anonymized cellphone records to understand the collective responses with respect to political events and under exogenous shocks such as emergencies. I lead the PITT Computational Social Dynamics Lab (PICSO LAB).
I am a computer scientist by training, and a computational social scientist working on questions like: "how would a society be informed?" "how do people share information, ideas and opinions in various contexts?" These questions have led me to explore analytical and computational techniques for mining heterogeneous, multi-relational, and semistructured data that can advance our understanding about structures in networked societies. I was a postdoctoral research fellow at the Institute for Quantitative Social Science, Harvard University and College of Computer and Information Science, Northeastern University.
My name is Esteban Moro and I am a researcher at Universidad Carlos III de Madrid in the GISC group. My field of research are complex systems. The fact that the systems under study are complex does not mean that its behavior cannot be understood or anticipated. I believe research must be interdisciplinary and close to real life problems and because of that, I do research in social networks, financial markets or viral marketing (complex enough!).
Olaf Sporns, Distinguished Professor, Psychological and Brain Sciences; Provost Professor, Psychological and Brain Sciences; Robert H. Shaffer Chair, Psychological and Brain Sciences×
The central goal of my research has been to characterize cannabinoid signaling in the brain. Exogenous cannabinoids are important drugs of abuse and have a role in human history dating back thousands of years. Only recently have we begun to learn how cannabinoids actually work in the body. Cannabinoid CB1 receptors are nearly ubiquitous in the CNS, by some counts the most numerous G protein-coupled receptors in the brain. They are involved in many important brain functions including (un-)learning and memory, epilepsy, motor control, vision, and probably much more. Much has been learned recently about the mechanisms by which cannabinoids act at the cellular level, but despite the detail, the picture is far from complete. By all accounts, CB1 receptors are part of a complex web of transporters, enzymes for production and breakdown of endocannabinoids, and signaling molecules, each subject to modulation. The precise workings of endocannabinoid signaling, and even the identity of the endocannabinoid at a given synapse, generally remain an open question. My primary approach is to use electrophysiology in combination with molecular biology, anatomy, endocannabinoid measurement, and microarray analysis to investigate specific mechanisms of cannabinoid signaling and their roles in health and disease.
Schools, Poster Session, and Satellite Co-Chairs:Antoine Allard, 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.
I am a network science PhD student at Northeastern University’s Network Science Institute studying computational social science under Dr. Brooke Foucault Welles. Using techniques from network science, natural language processing, and machine learning, I draw out stories from complex sociotechnical systems.
Carolina is studying how network science and digital traces can be applied to study economic activity and, more specifically, mobile money. She comes from a background in both Physics and International Relations. Currently, she is working on her dissertation and as a research assistant for Professor David Lazer on various projects.
I am an Assistant Professor in the Network Science Institute at Northeastern University--with appointments in Marine & Environmental Sciences, Physics, and Health Sciences (starting Sept. 2018)--and am also the Chief Data Scientist at Dharma.ai. My research spans a broad range of topics in complex systems and network science, including: infectious disease dynamics, forecasting and predictive modeling, complex network analysis, disease genomics and transcriptomics, outbreak surveillance, social networks, gene network evolution, and decision making under uncertainty. Our group, the Emergent Epidemics Lab, approaches these topics by investigating questions using mathematical and computational methods from biology, statistics, physics, applied mathematics, and computer science.
Adjacent Activities Committee:×
Alice joined IUNI as a research scientist in 2017 after completing her PhD in Applied Mathematics at Politecnico di Torino while working at the ISI Foundation. Her research interests include topological data analysis, computational topology and random models applied mainly to brain data and biomedicine. Her main interest is on developing new topological tools to complex systems and on studying their stability.
Jean-Gabriel Young, James S. McDonnell Foundation Postdoctoral Fellow, Center for the Study of Complex Systems, University of Michigan
- Location & Maps
Location for NetSci 2019:
University of Vermont Davis Center
590 Main St, Burlington, Vermont 05401, USA
Did you know? The Davis Center is the first student center in the U.S. to earn LEED Gold Certification.