Postdoctoral researcher at Institute of Economics, Polish Academy of Sciences and in Macroprudential Research Division at National Bank of Poland. She graduated in Mathematics (Jagiellonian University, Poland) and in Economics (University of Alcala, Spain). In 2017 she obtained Fulbright Advanced Research Award. In the United States, she carried out research on systemic risk and complex systems. Her doctoral dissertation was about the measurement and modeling of systemic risk using simulation methods and complex systems approach (the results to be published by Palgrave Macmillan US). Previously, she gained experience on agent-based modeling while working with Juan Luis Santos on the European Commission FP 7 MOSIPS project (http://www.mosips.eu/).

I live in Salento, a small land located between two seas in Southeastern Italy. I work as an educator in an adult school. My educational background includes a degree in Life Sciences. During my post-graduate training, I was involved in researching the genetic and molecular responses of cells to environmental and genomic stresses. Currently, I am interested in exploring theoretical biology and complex adaptive systems through agent-based modelling.

Sedar is a PhD student at the University of Leeds, department of Geography. He graduated in Computer Science at King’s College London 2018. From a very early stage of his degree, he focused on artificial intelligence planning implementations on drones in a search and rescue domain, and this was his first formal attempt to study artificial intelligence. He participated in summer school at Boğaziçi University in Istanbul working on programming techniques to reduce execution time. During his final year, he concentrated on how argumentation theory with natural language processing can be used to optimise political influence. In the midst of completing his degree, he applied to Professor Alison Heppenstall’s research proposal focusing on data analytics and society, a joint endeavour with the Alan Turing Institute and the Economic and Social Research Council. From 2018 - 2023 he will be working on his PhD at the Alan Turing Institute and Leeds Institute for Data Analytics.

Doctoral Fellow at LEMA research group, Urban and Environmental Engineering (UEE), University of Liege

I graduated Bachelor and Master studies at the University of Warsaw, obtaining the diploma in biology at College of Inter-Faculty Individual Studies in Mathematics and Natural Sciences (MISMaP). After graduation I worked as a freelancer in data science and statistics, then worked for 2 years as a data scientist in an IT startup and now I am working as a statistician in The Polish National Information Processing Institute (OPI PIB) in a group analysing condition of science and higher education in Poland. My interests: agent based modelling, evolutionary ecology, statistics, data science, sociology of science.

Dr. Roger Cremades is a complex systems scientist and heterodox global change economist integrating human-Earth interactions across systems and scales into modular quantitative tools, e.g. connecting drought risks in cities with land use at the river basin scale. He is elected Council member of the Complex Systems Society (2022-2025) and previously served as co-Chair of the Development Team of the Finance and Economics Knowledge-Action Network of Future Earth, the largest global research programme in global change (2020-2022). Roger coordinated research and co-production projects above €1M, and published in top journal like PNAS, Nature Climate Change, and Nature Geoscience. As a scientific modeler in the Social and Ecological Sciences, Roger integrates complex systems concepts into integrated assessment models of global change, with a focus on cities.

The future of CoMSES.Net, in Roger’s vision, is to augment its projection into a hub for discussing state-of-the-art approaches on modeling for the Social and Ecological Sciences, e.g. via bi-annual webinars, so that the Model Library becomes a lighthouse from where all communities developing, sharing, using, and reusing agent-based and other computational models also find valuable discussions to advance their research, education, and computational practice.