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I received a Ph.D. in Economics at the University of Namur (Belgium) in June 2012 with a thesis titled “Essays in Information Aggregation and Political Economics”.
After two years at the Research Center for Educational and Network Studies (Recens) of the Hungarian Academy of Sciences, I joined the Department of Economics “Marco Biagi” of the University of Modena and Reggio Emilia in January 2015 and then the Department of Agricultural and Food Sciences of the University of Bologna.
I am currently a Lecturer in Financial Computing at the Department Computer Science (Financial Computing and Analytics group) - University College London. Moreover I am an affiliated researcher of the DYNAMETS - Dynamic Systems Analysis for Economic Theory and Society research group and an affiliate member of the Namur Center for Complex Systems (Naxys).
My research interests concern the computational study of financial markets (microstructure, systemic properties and behavioral bias), of social Interactions on complex networks (theory and experiments), the evolution of cooperation in networks (theory and experiments) and the study of companies strategies in the digital economy.
I develop simulation tools for generating what-if scenarios for decision making. I predominantly use Agent-Based Modelling (ABM) technique as most of my simulations model complex systems. In some cases, I have extended existing tools with modifications to model the given system. Although the tools are meant for research purposes, I have followed industry friendly delivery mechanisms, such as unit-tests, automated builds and delivery on cloud platforms.
Furkan Gürsoy received the BS in Management Information Systems from Boğaziçi University, Turkey, and the MS in Data Science from İstanbul Şehir University, Turkey. He is currently a PhD Candidate at Boğaziçi University. He previously worked as an IS/IT Consultant and a Machine Learning Engineer with the industry for several years. He held a Visiting Researcher Position with IMT Atlantique, France, in 2020. His research interests include complex networks, machine learning, simulation, and broad data science.
network science, machine learning, simulation, data science.
Cristina Montañola Sales is an assistant professor at Institut Químic de Sarrià in Ramon Llull University, where she teaches subjects in ICT and statistics. She holds a PhD in Statistics and Operations Research and specializes in the investigation of novel quantitative methods for studying human behavior, such as agent-based models and spatio-temporal analysis. Her interdisciplinary research combines mathematics with social sciences, biomedicine and High-Performance Computing. She has studied various contexts, such as the dynamics of mobility of Gambian emigrants, demographic forecasting in South Korea, and ecological resilience of hunter-gatherers in India. Her research on tuberculosis transmissions and COVID-19 has advanced knowledge in epidemics, demographic dynamics and computational statistics. She has published articles and participated in international projects on simulation, parallel computing and global health.
validation, computer performace, epidemics, demography
BIGSSS-Departs PhD Fellow
Bremen International Graduate School of Social Sciences / Jacobs University (Germany)
PhD project: Residential Segregation and Intergenerational Immigrant Integration: A Schelling-Esser Model
Italian PhD fellow, fond of social complexity and agent-based modeling, applied to residential segregation and integration processes
Research Interests: Agent-based modeling, migrant integration, residential segregation
I am an environmental economist at UFZ - Helmholtz Centre for Environmental Research in Leipzig, Germany. I did my PhD (Dr. rer. pol.) in environmental economics at the Martin Luther University Halle-Wittenberg in 2017. Before that, I received my master’s (2013; economics) and bachelor’s degrees (2010; cultural studies) from the same university.
My research focus is on the economic analysis of agri-environmental policy instruments as means to navigate ecosystem service trade-offs in multifunctional landscapes. In this context, I am particularly interested in identifying policy instruments and instrument mixes allowing to align societal preferences with biophysical potential of landscapes to provide multiple ecosystem services. Here, the mutual relationship between regulatory and incentive-based instruments is of much interest. Using agent-based modelling, but also more qualitative approaches, I look at the emerging landscape-level patterns that result from various policy mixes given realistic descriptions of farmers’ behaviour and institutional settings.
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