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 Saramäki

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 Kéfi

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.

Tiago Pereira

Emergent hypernetworks in weakly coupled oscillators

Tiago Pereira is a Professor of Mathematics at the Universidade de São Paulo and a Visiting Professor at Imperial College London. His distinguished achievements include the International Incoming Marie Curie Fellowship, the Leverhulme Fellowship, and the Newton Advanced Fellowship from the Royal Society. He is a member of the Brazilian academy of sciences and a Bessel Fellow of the Humboldt Foundation and a Serrapilheira Fellowship recipient. Dr. Pereira received the Johannes Keppler Prize from the Brazilian Applied Mathematical Society in 2023 and the Marguerite Frank Award for Best Paper in 2022. In 2023, his student won Brazil's Best PhD Thesis in Applied Mathematics award.

Christof Schütte

Emergence in Multiscale Social Networks

Christof Schütte studied Mathematics, Physics and Computer Science in Paderborn and got his doctorate in Mathematics in Berlin in 1994. He has held a full professorship for Scientific Computing at FU Berlin since 2000. In 2015 he became President of the Zuse Institute Berlin, and in 2021 the head of the National High-Performance Computing Alliance in Germany. His research activities focus on data-driven modelling, simulation and optimization of complex processes with applications mainly to the life and social sciences. Christof Schuette acted as chair of the DFG research center MATHEON and as chair of the Cluster of Excellence MATH+.

Ginestra Bianconi

Topology and geometry shape the dynamics of higher-order networks

Ginestra Bianconi is Professor of Applied Mathematics in the School of Mathematical Sciences of Queen Mary University of London. She is member or the European Academy of Sciences. Currently she is Chief Editor of JPhys Complexity, Editor of PloSOne, and Scientific Reports. Awards: APS Fellow, Network Science Fellow and chair Franqui 2023.Her research activity on Statistical Mechanics and Network Science includes Network Theory and its interdisciplinary applications. She has formulated the Bianconi-Barabasi model that displays the Bose-Einstein condensation in complex networks. She has formulated the statistical mechanics of network ensembles and she has proven their non-equivalence. She has made important contribution on the study of critical phenomena on networks. In the last years, she has been focusing on multilayer networks, simplicial complexes, network geometry and topology, percolation, synchronization and network control. She is the author of the books Multilayer Networks: Structure and Function (Oxford University Press, 2018), Higher-order Networks: An introduction to simplicial complexes (Cambridge University Press, 2021) and editor of Networks of Networks in Biology (Cambridge University Press, 2021).

Anne Roefs

The network approach to understanding and treating psychopathology. Chasing rainbows or finding gold?

Anne’s research focuses mainly on the neuroscience and psychology of overweight, obesity and eating disorders. Funded by an NWO-VIDI grant, she examined how dietary restraint, bodyweight, and mindset influence neural representations of food, using fMRI. In 2023, she started a new project, funded by an NWO-VICI grant, focused on personalized understanding and treatment of overweight and obesity (www.theendofaverage.nl). The network approach to psychopathology features centrally in her recent research as well, and she is a co-PI in the Gravitation Project New Science of Mental Disorders (www.nsmd.eu). Life is not only work, and she loves a healthy lifestyle. As often as time allows, she is playing tennis or padel, or goes for a run, and recently started teaching kids the fundamentals of tennis.

Riet Van Bork

Measuring psychological constructs in the network framework

I research the contrast between traditional latent variable frameworks (where attributes cause shared variance among observed variables) and network perspectives (where direct causal relations between observed variables form clusters representing psychological attributes). My work combines empirical comparisons of these models with philosophical exploration of statistical interpretation, questioning how we conceptualize common factors, random variables, and what constitutes "observed" variables in psychological measurement.

Omid Ebrahimi

Towards precision in the diagnostic profiling of patients:

leveraging psychometric networks and symptom dynamics in the assessment and treatment of mental disorders

My research focuses on the development and maintenance of common mental health disorders (i.e. depression and anxiety) using multi-level and systems-based approaches. In particular, I examine how critical incidents occurring at the national and global level (e.g., infectious disease outbreaks, climate change, and economic recession) impact the development of common mental disorders and can alter human behaviour.