Lenka Zdeborová

Statistical Physics of Computation

Lenka Zdeborová is a Professor of Physics and Computer Science at École Polytechnique Fédérale de Lausanne, where she leads the Statistical Physics of Computation Laboratory. She received a PhD in physics from the University of Paris-Sud and Charles University in Prague in 2008. She spent two years in the Los Alamos National Laboratory as the Director's Postdoctoral Fellow. Between 2010 and 2020, she was a researcher at CNRS, working in the Institute of Theoretical Physics in CEA Saclay, France. In 2014, she was awarded the CNRS bronze medal, in 2016 Philippe Meyer prize in theoretical physics and an ERC Starting Grant, in 2018 the Irène Joliot-Curie prize, in 2021 the Gibbs lectureship of AMS and the Neuron Fund award. Lenka's expertise is in the application of concepts from statistical physics, such as advanced mean field methods, the replica method, and related message-passing algorithms, to problems in machine learning, signal processing, inference, and optimization. She enjoys erasing the boundaries between theoretical physics, mathematics and computer science.

Michael Macy

The Shallowness of Deep Division

Michael Macy is Distinguished Professor of Arts and Sciences at Cornell and Director of the Social Dynamics Lab. With support from the U.S. National Science Foundation, Google, Yahoo! Research, DARPA, IARPA, and the Korean National Research Foundation, his research team has used computational models, online laboratory experiments, and digital traces of device-mediated interaction to explore enigmatic social patterns, including network “wormholes,” diurnal rhythms, racial discrimination on Airbnb, lifestyle politics, the polarization of science, network mobility, and partisan unpredictability.

Jari Saramaki

Networks in Time and Space

Professor Jari Saramäki studies the dynamics of complex systems through temporal networks. His research combines theory and data to examine dynamic phenomena from social interaction patterns to the spread of information and diseases.

Linda Douw

Multiscale Network Neuroscience:

Connecting cells to circuits to networks in brain tumor patients

Linda Douw discovered network neuroscience during the final phase of her Master in Clinical Neuropsychology in Amsterdam. She continued to do a PhD on "Neural networks and brain tumors: the interplay between tumor, cognition, and epilepsy" at VU University Medical Center, which she finished in 2010. She then moved to Boston (US) for a postdoc at the Martinos Center for Biomedical Imaging (MGH/MIT/Harvard Medical School), further investigating multimodal network approaches to better understand brain tumors and epilepsy. In 2014, she moved back to Amsterdam to start her own lab, now called "Multiscale Network Neuroscience". She is currently an associate professor in the department of Anatomy and Neurosciences of the Amsterdam UMC, and leads a multidisciplinary research team. More information on the team's work can be found on www.multinetlab.com.

Iza Romanowska

Can the Past Save Our Future?

Iza Romanowska is a complexity scientist working at the intersection of computational and social sciences. Together with the team at the Social Resilience Lab, she applies computational methods to explore why some communities thrived for millennia while others succumbed to the first major crisis. Her expertise lies in agent-based modelling, a simulation technique used to understand the dynamics of ancient and modern socio-environmental systems. A graduate of the Institute for Complex System Simulation at the University of Southampton, she previously led the Social Science Simulation and Digital Humanities Research Group at the Barcelona Supercomputing Center before moving up north to Aarhus University, Denmark. Currently, she splits her time between the ERC project The Model City. Drivers and Mechanism of Urban Resilience and training the next generation of agent-based modellers in historical sciences.

Sonia Kefi

How Ecological Systems Respond to Stress

Sonia Kéfi is a researcher at the Centre National de la Recherche Scientifique (CNRS) and based at the Institut des Sciences de l’Evolution de Montpellier (ISEM), France. She is an ecologist interested in ecosystem complexity and how the architecture of ecological systems drives emergent properties such as stability and resilience. She combines theoretical models and data analysis from various ecosystems to address these questions.

Huijuan Wang

Temporal Higher-order Networks

Dr. Huijuan Wang is an Associate Professor in the department of Intelligent Systems at Delft University of Technology. Her research focuses on Network Data Science. She develops methodologies to model, control and predict dynamic processes on time-evolving complex networks. Her work addresses diverse applications, ranging from viral spreading, opinion interactions, social and financial contagion, cascades of failures to the organization of criminal activities. Dr. Wang has been a visiting scientist in the Department of Physics at Boston University (2011-2019), as well as in the Departments of Electrical Engineering at Stanford (2015) and Princeton (2022) Universities. She is the Co-Founder of the Dutch Network Science Society and serves as the Chair of the Netherlands Platform for Complex Systems. In addition, she is a board member of the Network Science Society and has been on the organizing board of the Conference on Complex Networks and its Applications since 2017.

Manlio De Domenico

Network Science in a Complex World:

Broken, Lost and Future Links

Manlio De Domenico is Associate Professor of Physics at the University of Padua, where he directs the Complex Multilayer Networks Lab. He is also Director of the Padua Center for Network Medicine, President of the Italian Chapter of the Complex Systems Society, co-founder and co-Director of the Mediterranean School of Complex Networks. His research explores collective phenomena in natural and artificial interdependent systems, with significant contributions to multilayer network modeling and analysis, applying these methods in biology, medicine, and epidemiology. His interdisciplinary work spans human mobility, disease spreading, connectomics, and network resilience, driving advancements in systems biology, systems medicine, and computational epidemiology. He has received prestigious awards, including the IUPAP Young Scientist Award in Statistical Physics and the German Physical Society's Young Scientist Award. He is also a prominent science communicator, leading initiatives like *Complexity Explained* and the #ComplexityThoughts newsletter.