Complex Networks XVII

Proceedings of the 17th Conference on Complex Networks, CompleNet 2026
Erscheinungsjahr 2026
ISBN: 978-3-032-39458-3
Verlag: Springer

Buch, Englisch, Format (B × H): 155 mm x 235 mm

Reihe: Springer Proceedings in Complexity

This volume contains the peer-reviewed proceedings of the 17th International Conference on Complex Networks (CompleNet 2026) and presents recent advances in the interdisciplinary field of Network Science.The selected contributions cover a broad range of topics, including computational social science, data science, network algorithms, network evolution, dynamics on and of networks, machine learning, recommender systems, urban systems, trade networks, and network theory. In addition to the contributed papers, the volume includes invited chapters that highlight emerging research directions and demonstrate the growing importance of network-based approaches in addressing scientific and societal challenges. By combining methodological innovations with applications to real-world complex systems, these proceedings provide a comprehensive overview of the current state of research in the field.

This proceedings volume is of interest to researchers, graduate students, and practitioners in Network Science, Complex Systems, Physics, Computer Science, Applied Mathematics, and related disciplines who seek an up-to-date perspective on recent developments in the field.

Zielgruppe

Research

Autoren/Hrsg.

Cardillo, Alessio

Cabrera, Carmen

Gomez Gardenes, Jesus

Soriano-Paños, David

Über Autor(innen)

Alessio Cardillo is a Ramón y Cajal Fellow at the University of Barcelona, where he is affiliated with the Department of Condensed Matter Physics and the University of Barcelona Institute of Complex Systems (UBICS). His research focuses on the study of complex systems whose interactions can be represented as networks, and also on the emergence of collective phenomena such as cooperation and synchronization in social and biological systems.Carmen Cabrera is Senior Lecturer in Geographic Data Science at the Geographic Data Science Lab (University of Liverpool), and an Honorary member of the Centre for Advanced Spatial Analysis (UCL). Her work sits at the intersection of geographic data science and computational social science. In her research, she uses high-resolution digital trace data and quantitative modelling to examine how disruptions, including extreme weather, pandemics and other shocks, reshape human mobility across urban space and population groups. Carmen collaborates with international and policy-facing partners, including various United Nations sections, national ministries and local governments, to advance the integration of digital trace mobility data into official statistics. She is a member of the UN Committee of Experts on Big Data and Data Science for Official Statistics and sits on the Council of the Complex Systems Society. Jesús Gómez-Gardeñes is Full Professor of Physics at the University of Zaragoza, where he leads the Group of Theoretical & Applied Modeling (GOTHAM Lab) at the Institute for Biocomputation and Physics of Complex Systems (BIFI). His research lies at the interface of statistical physics, nonlinear dynamics, and network science, with the goal of understanding the fundamental mechanisms governing the emergence of collective behavior in complex systems. By combining theoretical modeling, data analysis, and computational simulations, his work addresses a broad range of biological, social, and technological systems. His research has contributed to fields including epidemic spreading, synchronization, evolutionary dynamics, computational social science, neuroscience, and transportation systems. David Soriano Paños is a Senior Researcher at the University Rovira i Virgili. His research focuses on the study of coupled dynamical processes using nonlinear dynamics, statistical physics, and network science, with a primary focus on the multiscale characterization of infectious diseases. His research spans epidemic dynamics at the population level, within-host viral evolution, and the interplay between these scales to understand how viral evolution shapes the macroscopic impact of infectious diseases. Alongside these fundamental contributions, his work has informed public health interventions to manage dengue and COVID-19 epidemic outbreaks.