Community

Kevin Ash Member since: Friday, July 06, 2018 Full Member

PhD, Geography, Univ. of South Carolina, MS, Geography, Univ. of Florida, BA, Geography, Univ. of Oklahoma

Federico Bianchi Member since: Monday, April 14, 2014 Full Member

Ph.D., Economic Sociology and Labour Studies, University of Milan - University of Brescia (Italy), M.A., Sociology, University of Turin (Italy), B.A., Philosophy, University of Milan (Italy)

Simone Righi Member since: Friday, June 08, 2018

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.

Tatiana Filatova Member since: Tuesday, October 04, 2011 Full Member

PhD (Cum Laude), Department of Water Engineering and Management, University of Twente, The Netherlands

I am Professor in Computational Resilience Economics at the University of Twente (the Netherlands), which I joined in 2010. In September 2017 I also joined University of Technology Sydney (Australia) as Professor of Computational Economic Modeling working with spatial simulation models to study socioeconomic impacts of disasters and emergence of resilience across scales. I was honored to be elected as a Member of the De Jonge Akademie of the Royal Dutch Academy of Sciences (DJA/ KNAW in 2016) and of Social Sciences Council (SWR/KNAW in 2017). From 2009 to 2015 I have been working part-time as an economist at Deltares – the leading Dutch knowledge institute in the field of water management – specializing in economics of climate change, with focus on floods and droughts management.

I am interested in the feedbacks between policies and aggregated outcomes of individual decisions in the context of spatial and environmental policy-making. The issue of social interactions and information diffusion through networks to affect economic behavior is highly relevant here. My research line focuses on exploring how behavioral changes at micro level may lead to critical transitions (tipping points/regime shifts) on macro level in complex adaptive human-environment systems in application to climate change economics. I use agent-based modelling (ABM) combined with social science methods of behavioral data collection on individual decisions and social networks. This research line has been distinguished by the NWO VENI and ERC Starting grants and the Early Career Excellence award of the International Environmental Modeling Society (iEMSs). In 2018 I was invited to serve as the Associate Editor of the Environmental Modelling & Software journal, where I have been a regular Member of the Editorial Board since 2013.

Andreas Angourakis Member since: Wednesday, February 03, 2016

Master Degree in Prehistorical Archaeology (Autonomous University of Barcelona), Degree in Sociology (Autonomous University of Barcelona), Degree in Humanities (Autonomous University of Barcelona)

Moira Zellner Member since: Friday, December 06, 2013 Full Member

PhD, Urban and Regional Planning, University of Michigan, Ann Arbor

Dr. Moira Zellner is an associate professor at the University of Illinois at Chicago in the Department of Urban Planning and Policy, the director of the Urban Data Visualization lab, and is a research associate professor in the Institute for Environmental Science and Policy at UIC. Dr. Zellner has served as Principal Investigator and Co-Investigator in interdisciplinary projects examining how specific policy, technological and behavioral factors influence the emergence and impacts of a range of complex environmental problems, where interaction effects make responsibilities and burdens unclear. Her research also examines the value of complexity-based modeling for participatory policy exploration and social learning with stakeholders and decision-makers. Dr. Zellner also teaches a variety of workshops on complexity-based modeling of socio-ecological systems, for training of both scientists and decision-makers.

Applications of agent-based modeling to urban and environmental planning

Gunnar Dressler Member since: Monday, February 22, 2016 Full Member Reviewer

PhD Applied Systems Science, Dipl. Biomathematics
  • since April 2017: PostDoc at the Department of Ecological Modeling, Helmholtz-Centre for Environmental Research - UFZ
  • since January 2015: Member of the Junior Research Group POLISES - Global food security policies and their social-ecological side effects in regions prone to global change.
  • 2012-2017 PhD student at the Department of Ecological Modeling, Helmholtz-Centre for Environmental Research - UFZ
  • 2006-2011 Diploma in Biomathematics, Ernst-Moritz-Arndt-University of Greifswald
  1. Dynamics of socio-ecological resource use systems
    • Pasture use in dryland grazing systems under change, effects of new technologies and policy instruments, emergence of polarization between pastoralists (e.g. in terms of livestock numbers).
    • Thresholds of disaster management performance under change, loss of manpower, the role of information as critical resource.
  2. Human decision making in agent-based models.
  3. Remote sensing and GIS.

James Howard Member since: Friday, February 01, 2019 Full Member

Ph.D., Public Policy, University of Maryland Baltimore County, M.P.A., Public Policy and Administration, University of Baltimore, B.S., Mathematics, University of Maryland

I am a scientist at the Johns Hopkins Applied Physics Laboratory. Previously, I worked for the Board of Governors of the Federal Reserve System as an internal consultant on statistical computing. I have also been a consultant to numerous government agencies, including the Securities and Exchange Commission, the Executive Office of the President, and the United States Department of Homeland Security. I am a passionate educator, teaching mathematics and statistics at the University of Maryland University College since 2010 and have taught public management at Central Michigan University, Penn State, and the University of Baltimore.

I am fortunate to play in everyone else’s backyard. My most recent published scholarship has modeled the population of Earth-orbiting satellites, analyzed the risks of flood insurance, predicted disruptive events, and sought to understand small business cybersecurity. I have written two books on my work and am currently co-editing two more.

In my spare time, I serve Howard County, Maryland, as a member of the Board of Appeals and the Watershed Stewards Academy Advisory Committee of the University of Maryland Extension. Prior volunteer experience includes providing economic advice to the Columbia Association, establishing an alumni association for the College Park Scholars Program at the University of Maryland, and serving on numerous public and private volunteer advisory boards.

Caryl Benjamin Member since: Wednesday, December 12, 2012

BS Community Development

Community assembly after intervention by coral transplantation

The potential of transplantation of scleractinian corals in restoring degraded reefs has been widely recognized. Levels of success of coral transplantation have been highly variable due to variable environmental conditions and interactions with other reef organisms. The community structure of the area being restored is an emergent outcome of the interaction of its components as well as of processes at the local level. Understanding the
coral reef as a complex adaptive system is essential in understanding how patterns emerge from processes at local scales. Data from a coral transplantation experiment will be used to develop an individual-based model of coral community development. The objectives of the model are to develop an understanding of assembly rules, predict trajectories and discover unknown properties in the development of coral reef communities in the context of reef restoration. Simulation experiments will be conducted to derive insights on community trajectories under different disturbance regimes as well as initial transplantation configurations. The model may also serve as a decision-support tool for reef restoration.

Talal Alsulaiman Member since: Friday, February 27, 2015

Bachelor of Science in Systems Engineering, Master of Science in Industrial Engineering, Master of Science in Financial Engineering

In this paper, we explore the dynamic of stock prices over time by developing an agent-based market. The developed artificial market comprises of heterogeneous agents occupied with various behaviors and trading strategies. To be specific, the agents in the market may expose to overconfidence, conservatism or loss aversion biases. Additionally, they may employ fundamental, technical, adaptive (neural network) strategies or simply being arbitrary agents (zero intelligence agents). The market has property of direct interaction. The environment takes the form of network structure, namely, it takes the manifestation of scale-free network. The information will flow between the agents through the linkages that connect them. Furthermore, the tax imposed by the regulator is investigated. The model is subjected to goodness of fit to the empirical observations of the S\&P500. The fitting of the model is refined by calibrating the model parameters through heuristic approach, particularly, scatter search. Conclusively, the parameters are validated against normality, absence of correlations, volatility cluster and leverage effect using statistical tests.

This website uses cookies and Google Analytics to help us track user engagement and improve our site. If you'd like to know more information about what data we collect and why, please see our data privacy policy. If you continue to use this site, you consent to our use of cookies.