Tina Eliassi – Rad is the inaugural President Joseph E. Aoun Professor at Northeastern University. She is also a core faculty member at Northeastern’s Network Science Institute and the Institute for Experiential AI. In addition, she is an external faculty member at the Santa Fe Institute and the Vermont Complex Systems Center. 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 at the intersection of data mining, machine learning, and network science. She has over 170 peer-reviewed publications (including a few best paper and best paper runner-up awards); and has given over 270 invited talks and 14 tutorials. 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, cyber situational awareness, drug discovery, democracy and online discourse, and ethics in machine learning. Her algorithms have been incorporated into systems used by governments and industry (e.g., IBM System G Graph Analytics), as well as open-source software (e.g., Stanford Network Analysis Project). In 2017, Tina served as the program co-chair for the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (a.k.a. KDD, which is the premier conference on data mining) and as the program co-chair for the International Conference on Network Science (a.k.a. NetSci, which is the premier conference on network science). In 2020, she served as the program co-chair for the International Conference on Computational Social Science (a.k.a. IC2S2, which is the premier conference on computational social science). Tina received an Outstanding Mentor Award from the U.S. Department of Energy’s Office of Science in 2010, became an ISI Foundation Fellow in 2019, was named one of the 100 Brilliant Women in AI Ethics in 2021, received Northeastern University’s Excellence in Research and Creative Activity Award in 2022, was awarded the Lagrange Prize-CRT Foundation in 2023, and was elected Fellow of the Network Science Society in 2023.

David Gruber is Presidential Professor of Biology and Environmental Science at Baruch College, City University of New York, and serves on the faculty of the Ph.D. Program in Biology at the CUNY Graduate Center and the CUNY Macaulay Honors College. He is also an Explorer for National Geographic, a Research Associate in Invertebrate Zoology at the American Museum of Natural History and an Adjunct Faculty member at the John B. Pierce Laboratory of the Yale School of Medicine. His interdisciplinary research pertains to marine biology, genomics/transcriptomics of uncharacterized marine organism, deep-sea ecology, soft robotics, photosynthesis, biofluorescence, bioluminescence and applying advanced machine learning techniques to better understand whale bioacoustics.

Iain Couzin is Director of the Max Planck Institute of Animal Behavior, Department of Collective Behaviour, Co-Director of the DFG Excellence Cluster ‘Centre for the Advanced Study of Collective Behaviour’ and Chair of Biodiversity and Collective Behaviour at the University of Konstanz, Germany. His work aims to reveal the fundamental principles that underlie evolved collective behavior, and consequently his research includes the study of a wide range of biological systems, from insect swarms to fish schools and primate groups. He has pioneered the study of collective sensing, information processing and decision-making in animal groups. In addition to the various awards already received, in 2018 he obtained the Clarivate Analytics (Web of Science) Global Highly Cited Researcher.

César A. Hidalgo leads the Collective Learning group at The MIT Media Lab and is an Associate Professor of Media Arts and Sciences at MIT. Hidalgo’s work focuses on understanding how teams, organizations, cities, and nations learn. At the Collective Learning group, Hidalgo studies knowledge flows and also creates software tools to facilitate learning in organizations. Hidalgo’s academic publications have been cited more than 12,000 times and his online systems have received more than 100 million pageviews and numerous awards. Hidalgo’s latest book, Why Information Grows (Basic Books, 2015), has been translated to over ten languages. Hidalgo is also the co-author of The Atlas of Economic Complexity (MIT Press, 2014), and a co-founder of Datawheel LLC, a company that has professionalized the creation of large data visualization engines. Hidalgo lives in Somerville Massachusetts with his wife Anna and their daughter Iris.

Danielle S. Bassett is Eduardo D. Glandt Faculty Fellow Associate Professor at the University of Pennsylvania. With her group Danielle Bassett studies biological, physical, and social systems by using and developing tools from network science and complex systems theory. Their broad goal is to isolate problems at the intersection of basic science, engineering, and clinical medicine that can be tackled using systems-level approaches. Bassett’s group is currently studying dynamic changes in network architecture, the interaction between topological properties of networks and physical or other constraints, and the influence of network topology on signal propagation and system function. They use a combination of data analysis, mathematical modeling, and empirical studies to investigate these phenomena.

John Brownstein, Ph.D. is Professor of Pediatrics and Biomedical Informatics at Harvard Medical School and is the Chief Innovation Officer of Boston Children’s Hospital. He also directs the Computational Epidemiology Group at the Children’s Hospital Informatics Program in Boston. He was trained as an epidemiologist at Yale University. Overall, his research agenda aims to have translation impact on the surveillance, control and prevention of disease. He has been at the forefront of the development and application of digital health tools including HealthMap.org, an internet-based global infectious disease intelligence system. Dr. Brownstein has advised the World Health Organization, Institute of Medicine, the US Department of Health and Human Services, and the White House on real-time public health surveillance. He has authored over 200 peer-reviewed articles which have provided foundational learnings for the emerging field of digital epidemiology.

Jure Leskovec is Assistant Professor of Computer Science at Stanford University where is a member of the InfoLab and the AI lab. His research focuses on mining and modeling large social and information networks, their evolution, and diffusion of information and influence over them.

Panos Ipeirotis is Associate Professor and George A. Kellner Faculty Fellow at the Department of Information, Operations, and Management Sciences at Leonard N. Stern School of Business of New York University. His recent research interests focus on crowdsourcing and on mining user-generated content on the Internet.

Mark Newman with his group conducts research on the structure and function of networks, particularly social and information networks, that are studied using a combination of empirical methods, analytics, and computer simulation. Among other things, he has investigated scientific coauthorship networks, citation networks, email networks, friendship networks, epidemiological contact networks, and animal social networks; his group studied fundamental network properties such as degree distributions, centrality measures, assortative mixing, vertex similarity, and community structure, and made analytic or computer models of disease propagation, friendship formation, the spread of computer viruses, the Internet, and network navigation algorithms.

Duncan J. Watts is a principal researcher at Microsoft Research and a founding member of the MSR-NYC lab. From 2000-2007, he was a professor of Sociology at Columbia University, and then, prior to joining Microsoft, a principal research scientist at Yahoo! Research, where he directed the Human Social Dynamics group. Watts describes his research as exploring the “role that network structure plays in determining or constraining system behavior, focusing on a few broad problem areas in social science such as information contagion, financial risk management, and organizational design”. More recently he has attracted attention for his modern-day replication of Stanley Milgram’s small world experiment using email messages and for his studies of popularity and fads in online and other communities. The six degrees research is based on his 1998 paper with Steven Strogatz in which the two presented a mathematical theory of the small world phenomenon.

Riccardo Luna is an Italian journalist and writer, director of the online magazine “CheFuturo!” and was formerly the first director of Wired Italian edition. Since 2011 he has written about innovation in La Repubblica newspaper. He’s also a columnist on Wired, Vanity Fair and Traveller. Since 2012 he is Chairman of Wikitalia, an association whose aim is to spread transparency, open data and participation in Italian politics by the use of the Internet. He is also coordinator of the Expo2015 Innovation Advisory Board and Board Member of Oxfam and Building Green Future.

Lada Adamic is Associate Professor at the School of information & Center for the study of Complex Systems of the University of Michigan. She studies the structure and dynamics of social and information networks, with particular emphasis on information diffusion, expertise sharing and online communities.

Xavier Gabaix is Associate Professor of Finance at the NYU Stern School of Business. His research interests focus on asset pricing, executive pay, the causes and consequences of seemingly irrational behavior, the origin of scaling laws in economics and macroeconomics.

Albert Laszlo Barabasi is a Distinguished University Professor at Northeastern University, Boston where he directs the Center for Complex Networks Research and holds appointments in the Departments of physics, Computer Science and Biology, as well as in the Department of Medicine, Harvard Medical School and Brigham and Women Hospital and is a member of the Center for Cancer Systems Biology at Dana Farber Cancer Institute. Barabasi’s work on complex networks led to the discovery of scale-free networks and he proposed the Barabasi-Albert model to explain their widespread emergence in natural, technological and social systems, from the cellular telephone to the WWW or online communities.

Professor of Biomedical Engineering and Co-Director of the Center for BioDynamics at Boston University. He is one of the founders of the emerging field of synthetic biology and a pioneering researcher in systems biology, stochastic resonance, biological dynamics and neurostimulation.

Full professor at the University La Sapienza in Rome where he teached probability theory, is member of the Accademia Nazionale dei Lincei and of the National Academy of Science. Parisi did research in several fields of Physics and in particular in Physics of disordered systems and statistical mechanics. He authored and co-authored a number of scientific books like La Chiave, la luce e l’ubriaco and Statistical Physics. Giorgio Parisi was later awarded the 2021 Nobel Prize in Physics jointly with Klaus Hasselmann and Syukuro Manabe for their contributions to the theory of complex systems.