Sandro Azaele (University of Padua, Italy)
Sandro Azaele earned his Ph.D. in Physics in 2007 at the University of Padua (Italy) working at the crossroads between statistical physics and ecology. Then, he moved to Princeton University as a research associate. After several international experiences, first at the University of Leeds as a Research Fellow (2009-2012), then as a Lecturer in Applied Mathematics (2012-2016), and eventually as a Visiting Fellow at the Isaac Newton Institute for Mathematical Sciences in Cambridge, in 2019 he moved back to the University of Padua as Associate Professor.
He is internationally recognized for his expertise in statistical mechanics, ranging from probabilistic approaches to Dynamical Mean-Field Theory, with applications in theoretical ecology.
Hélène Morlon (IBENS, Paris)
Hélène Morlon obtained her Ph.D. in “Environmental Sciences” in 2005 at the University of Bordeaux I (France). Then, she spent five years as a postdoctoral researcher in the US between the University of California (Green lab and Potts lab), the University of Oregon (Green lab and Bohannan lab), and the University of Pennsylvania. In 2010 she obtained a tenured position at CNRS, in Paris, and a year later she became an associate member of the Center for Interdisciplinary Research in Biology, affiliated with Collège de France. Since 2014 she is Research Director (DR1) of CNRS and leads her team at the Institut de Biologie de l’Ecole Normale Supérieure. She combines her expertise in mathematics, evolution as well as bioinformatics to study macroevolution, spatial distribution of phylogenetic diversity, and microbial communities.
Maria del Rio Chanona (University College London)
Maria del Rio Chanona is Lecturer in the Computer Science department at the University College London. Her research draws from network science, machine learning, and agent-based modelling and focuses on the future of work, the net-zero transition, and the economic impact of the Covid-19 pandemic. Maria has a PhD in Mathematics from the University of Oxford, where she was part of the Complexity Economics group of the Institute for New Economic Thinking at the Oxford Martin School. Maria was a JSMF research fellow at the Complexity Science Hub, Vienna and a visiting scholar at the Harvard Kennedy School. She has worked alongside international policy organisations, including the International Monetary Fund and the International Labour Organisation. Before her postgraduate studies, Maria did her undergraduate studies in Physics at UNAM, Mexico.
Tim Rogers (University of Bath)
Tim Rogers is a Professor of Mathematics at the University of Bath. His research interests include graphs and networks, applied stochastic processes, and emergent phenomena. He is particularly interested in understanding and predicting the behaviour of complicated random events and processes, in particular when there is network or spatial structure involved. Most of his work is connected to the idea of emergence: how large scale order can be created out of the random interactions of individual particles or organisms. The problems come from a wide range of sources including ecology, biochemistry, random matrix theory, social dynamics, and stochastic processes.
Fabio Caccioli (University College London)
Fabio Caccioli is a Professor of Complex Systems at University College London (UCL). Before joining UCL, he served as a Research Associate at the Centre for Risk Studies, University of Cambridge, and was a Postdoctoral Fellow at the Santa Fe Institute. Fabio earned his PhD in Statistical Physics from the International School for Advanced Studies (SISSA) in Trieste, Italy. His research explores the application of complex systems and statistical mechanics to economic and financial systems, with a particular focus on systemic risk. Other research interests include complex networks, the science of science, and non-equilibrium statistical mechanics.
Marco Pangallo (CENTAI)
Marco Pangallo is a research scientist at CENTAI (Center for Artificial Intelligence), a newly established research institute that aims at combining independent research on artificial intelligence and complex systems with industrial applications. Previously, he was a JSMF Postdoctoral Fellow at the Sant’Anna School for Advanced Studies, Italy. Marco obtained his PhD in Mathematics at the University of Oxford and was part of the Complexity Economics group at the Oxford Martin School’s Institute for New Economic Thinking. Marco is generally interested in understanding the economy quantitatively through a combination of data-driven and theoretical approaches. He believes that traditional economic models – based on optimization and equilibrium – are not best suited to quantitatively account for the complexity of the economy. Instead, agent-based models are the best tool to assimilate increasingly available granular data and produce more reliable economic forecasts.
Mateusz Wilinski (Tampere University, Finland)
Mateusz earned a B.S. in Mathematics and a M.S. in both Mathematics and Physics from the University of Warsaw and a Ph.D. in Physics from the University of Warsaw. He then moved to Italy, to Scuola Normale Superiore di Pisa where he worked on clustering algorithms for networks. After that, he spent three years in the Theoretical Division at the Los Alamos National Laboratory, working mostly on learning and inference methods for dynamics on networks. Finally, he received the Marie Sklodowska Currie Actions Fellowship and moved to Tampere University in Finland. His current project focuses on using deep learning to build data-driven, intelligent agents for limit order book simulation. He has broad interests including network science, machine learning, statistical physics, epidemic modelling and financial markets. In addition to his scientific path, he has extensive experience in working for the industry, which includes hedge funds, investment banks and fintech companies.