Albert-Laszlo Barabasi

Northeastern University

Albert-László Barabási is a network scientist and current Distinguished Professor and Director of Northeastern University's Center for Complex Network Research (CCNR). He focuses on a wide range of topics, including unveiling the structure of the brain to treating diseases using network medicine and the emergence of success in art to how does science really works. His work has helped unveil the hidden order behind various complex systems using the quantitative tools of network science, a research field that he pioneered, and lead to the discovery of scale-free networks, helping explain the emergence.

COURSE

NETWORK SCIENCE PRINCIPLES

June 22-24, 2020

Baruch Barzel

Bar-Ilan University

Baruch Barzel is a physicist and applied mathematician at Bar-Ilan University. His main research focuses on the dynamic behavior of complex networks, uncovering universal principles that govern the dynamics of diverse systems, such as disease spreading, gene regulatory networks, protein interactions or population dynamics. Barzel is also an active public lecturer, presenting a weekly corner on Israel National Radio.

COURSE

NETWORK SCIENCE PRINCIPLES

June 22-24, 2020

Noshir Contractor

Northwestern University

Noshir Contractor is the Jane S. & William J. White Professor of Behavioral Sciences in the School of Engineering, the School of Communication and the Kellogg School of Management and Director of the Science of Networks in Communities (SONIC) Research Group at Northwestern University. He is investigating how social and knowledge networks form – and perform – in contexts including business, scientific communities, healthcare and space travel. His research has been funded continuously for 25 years by the U.S. National Science Foundation with additional funding from the U.S. National Institutes of Health, NASA, DARPA, Army Research Laboratory and the Bill & Melinda Gates Foundation.

COURSE

SOCIAL NETWORKS THEORIES & METHODS

June 22-24, 2020

Santo Fortunato

Indiana University

Santo Fortunato is the director of the Center for Complex Networks and Systems Research and the Network Science Institute at Indiana University. His current focus areas are network science, especially network community detection, computational social science, and science of science. His research has been published in leading journals, including Nature, Science, PNAS, Nature Communications, Physical Review Letters, and Reviews of Modern Physics. His Physics Reports review article Community detection in graphs is one of the best known and most cited papers in network science.

COURSE

COMMUNITY STRUCTURES

June 29-July 1, 2020

Trey Ideker

UC San Diego

Trey Ideker is a Professor of Medicine at UC San Diego. He is the Director of the National Resource for Network Biology, the Cancer Cell Map Initiative and the Psychiatric Cell Map Initiative. Ideker is a pioneer in using genome-scale measurements to construct network models of cellular processes and disease and has founded software tools including the Cytoscape ecosystem for biological network analysis, which has been cited >13,000 times. His work has been featured in news outlets such as The Scientist, San Diego Union-Tribune, Forbes magazine, NPR, and The New York Times.

COURSE

BIOLOGICAL NETWORKS

June 24-26, 2020

Dima Krioukov

Northeastern University

Dmitri Krioukov is an Associate Professor at the Departments of Physics, Mathematics, and Electrical & Computer Engineering at Northeastern University, and a core member of the Network Science Institute. His research deals with theory and fundamental aspects of complex networks. Research topics of particular interest to the lab are latent network geometry, maximum-entropy ensembles of random graphs and simplicial complexes, random geometric graphs, causal sets, navigation in networks, and fundamental aspects of network dynamics. He gained national fame as the “Physicist who used a 4-page scientific argument to avoid a traffic ticket.

COURSE

NETWORK GEOMETRY

July 1-3, 2020

Jure Leskovec

Stanford University

Jure Leskovec is Associate Professor of Computer Science at Stanford University, Chief Scientist at Pinterest, and investigator at Chan Zuckerberg Biohub. His research focuses on machine learning and data mining large social and information networks, their evolution, and the diffusion of information and influence over them. Computation over massive data is at the heart of his research and has applications in computer science, social sciences, economics, marketing, and healthcare. His research has won several awards including a Lagrange Prize, Microsoft Research Faculty Fellowship, the Alfred P. Sloan Fellowship, and numerous best paper awards.

COURSE

MACHINE LEARNING IN NETWORKS

June 29-July 1, 2020

Alina Lungeanu

Northwestern University

Alina Lungeanu is a Research Assistant Professor in the School of Communication at Northwestern University. Her research investigates diversity and leadership in teams, and their impact on team innovation and performance. Lungeanu combines insights from social science and social network theories and methods to examine the role of individual, team and social network features for team innovation and performance. Her work is funded by grants from the National Science Foundation and National Institutes of Health and has been published in leading social science journals such as the American Behavioral Scientist, Network Science, Implementation Science, and Communication Methods and Measures.

COURSE

SOCIAL NETWORKS THEORIES & METHODS

June 22-24, 2020

Tijana Milenkovic

University of Notre Dame

Dr. Tijana Milenkovic is an Associate Professor of Computer Science and Engineering at the University of Notre Dame. At Notre Dame, Milenkovic leads the Complex Networks (CoNe) Lab, whose research focuses on developing computational methods for modeling complex (large, noisy, heterogeneous, and dynamic) real-world systems as networks and for efficiently mining the networks to learn how the systems function. Her research efforts have resulted in three book chapters and over 37 journal publications (e.g., in Science, Nature's Scientific Reports, PNAS, or Bioinformatics), along with a number of conference papers (e.g., in ISMB/ECCB).

COURSE

BIOLOGICAL NETWORKS

June 24-26, 2020

Yamir Moreno

ISI, University of Zaragoza

Yamir Moreno is the Director of the Institute for Biocomputation and Physics of Complex Systems (BIFI), the head of the Complex Systems and Networks Lab (COSNET) and Professor of Physics at the Department of Theoretical Physics of the Faculty of Sciences, University of Zaragoza. . During the last years, he has been working on several problems such as: the study of nonlinear dynamical systems coupled to complex structures, transport processes and diffusion with applications in communication and technological networks, dynamics of virus and rumors propagation, game theory, systems biology (the TB case), the study of more complex and realistic scenarios for the modeling of infectious diseases, synchronization phenomena, the emergence of collective behaviors in biological and social environments, the development of new optimization data algorithms and the structure and dynamics of socio-technical and biological systems. He has published more than 200 scientific papers with a total of 18700+ citations and h-index=54 (ISI WoK) or 31500+ and 65 (Google Scholar).

COURSE

NETWORK PROCESSES & DYNAMICS

June 24-26, 2020

Tiago Peixoto

Central European University

Tiago P. Peixoto is a physicist and is currently an Associate Professor at the Department of Network and Data Science at the Central European University and external researcher at the ISI Foundation. He was a Humboldt Foundation fellow, and the recipient of the Erdős-Rényi Prize (2019) awarded by the Network Science Society. His research focuses on characterizing, identifying and explaining large-scale patterns found in the structure and function of complex network systems — representing diverse phenomena with physical, biological, technological, or social origins — using principled approaches from statistical physics, nonlinear dynamics and Bayesian inference.

COURSE

COMMUNITY STRUCTURES

June 29-July 1, 2020

Bruno Ribeiro

Purdue University

Bruno Ribeiro is an Assistant Professor in the Department of Computer Science at Purdue University. He obtained his Ph.D. at the University of Massachusetts Amherst and did his postdoctoral studies at Carnegie Mellon University from 2013-2015. His research interests are in deep learning and data mining, with a focus on sampling and modeling relational and temporal data.

COURSE

MACHINE LEARNING IN NETWORKS

June 29-July 1, 2020

M. Ángeles Serrano

University of Barcelona

M. Ángeles Serrano is an ICREA Research Professor at the Department of Condensed Matter Physics of the University of Barcelona and External Faculty at the Complexity Science Hub Vienna CSH. She is interested in unraveling the universal principles and laws underlying the structure, function, and evolution of complex networks. Her research covers theoretical developments and applications to a variety of real systems, from international trade to the Internet and the brain. Serrano is a founding member of Complexitat, the Catalan network for the study of complex systems, and a promoter member of UBICS, the Universitat de Barcelona Institute of Complex Systems.

COURSE

NETWORK GEOMETRY

July 1-3, 2020

Olaf Sporns

Indiana University

Olaf Sporns is a Distinguished Professor in the Department of Psychological and Brain Sciences at Indiana University in Bloomington. His main research area is theoretical and computational neuroscience, with a focus on complex brain networks. He has authored over 160 peer-reviewed publications as well as the recent books “Networks of the Brain” and “Discovering the Human Connectome”, both published by MIT Press. He is also the founding editor of the academic journal Network Neuroscience, published by MIT Press.

COURSE

NETWORK NEUROSCIENCE

July 1-3, 2020

Petra Vértes

University of Cambridge

Petra Vértes is an MRC fellow in Bioinformatics at the Brain Mapping Unit (BMU) at Cambridge University. Her work builds on methods and concepts from physics and bioinformatics and applies them to fundamental problems in neuroscience. She is particularly interested in the structure-function relationship in brain networks, from the microscopic scale of neurons to the large-scale connectivity of brain regions, in both health and disease. She is also one of the co-founders and organizers of the Cambridge Networks Network (CNN), a forum for academics across different disciplines who share an interest in Network Science.

COURSE

NETWORK NEUROSCIENCE

July 1-3, 2020

Alessandro Vespignani

Northeastern University

Alessandro Vespignani is a physicist, best known for his work on complex networks, and particularly for work on the applications of network theory to the spread of disease, applications of computational epidemiology, and for studies of the topological properties of the Internet. He is currently the Sternberg Family Distinguished University Professor of Physics, Computer Science and Health Sciences at Northeastern University, where he is the director of the Network Science Institute. Vespignani has published 180+ peer reviewed papers in top rated scientific journals, including Nature, Science and PNAS that have accrued more than 50,000 citations according to the Google Scholar database.

COURSE

NETWORK PROCESSES & DYNAMICS

June 24-26, 2020

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