Displaying 10 of 71 results system clear

Juan Ocampo Member since: Wed, Sep 11, 2019 at 07:52 PM Full Member

PhD Candidate at Lund School of Economics and Management - Sweden, (2019) MSocSc Organizational Innovation and Entrepreneurship, Copenhagen Business School, (2016) MSc in Industrial Engineering, Universidad de los Andes, (2012) Industrial Engineering, Universidad de los Andes, Colombia

I am Colombian with passion for social impact. I believe that change starts at the individual, community, local and then global level. I have set my goal in making a better experience to whatever challenges I encounter and monetary systems and governance models is what concerns me at the time.

In my path to understanding and reflecting about these issues I have found my way through “Reflexive Modeling”. Models are just limited abstractions of reality and is part of our job as researchers to dig in the stories behind our models and learn to engage in a dialogue between both worlds.

Technology empowers us to act locally, autonomously and in decentralized ways and my research objective is to, in a global context, find ways to govern, communicate and scale the impact of alternative monetary models. This with a special focus on achieving a more inclusive and community owned financial system.

As a Ph.D. fellow for the Agenda 2030 Graduate School, I expect to identify challenges and conflicting elements in the sustainability agenda, contribute with new perspectives, and create solutions for the challenges ahead

Doug Salt Member since: Wed, Dec 06, 2017 at 06:03 PM Full Member Reviewer

PhD, BSc (Hons)

I obtained a PhD in database information theory from the University of the West of Scotland in 2015, and have been a researcher at the James Hutton Institute ever since. My areas of research are agent-based-modelling (ABM), data curation, effective use of infrastructure as a service (IaaS), and semantic information representation and extraction using formal structures such as computerised ontologies, relational databases and any other structured or semi-structured data representations. I primarily deal with social and agricultural models and was originally taken on in the role of knowledge engineer in order to create the ontology for the H2020 project, Green Lifestyles, Alternative Models and Upscaling Regional Sustainability (GLAMURS). Subsequent work, for the Scottish Government has involved the use of IaaS, more commonly referred to as the “cloud” to create rapidly deployable and cheap alternatives to in-house high-performance computing for both ABM and Geographical Information System models.

It is the mixture of skills and interests involving modelling, data organisation and computing infrastructure expertise that I believe will be highly apposite in the duties associated with being a member of the CoMSES executive. Moreover, prior to joining academia, I spent about 25 years as a developer in commercial IT, in the agricultural, entertainment and banking sectors, and feel that such practical experience can only benefit the CoMSES network.

James Howard Member since: Fri, Feb 01, 2019 at 12:41 PM 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.

Xiaotian Wang Member since: Fri, Mar 28, 2014 at 02:23 AM

PHD of Engineering in Modeling and Simulation, Proficiency in Agent-based Modeling

Social network analysis has an especially long tradition in the social science. In recent years, a dramatically increased visibility of SNA, however, is owed to statistical physicists. Among many, Barabasi-Albert model (BA model) has attracted particular attention because of its mathematical properties (i.e., obeying power-law distribution) and its appearance in a diverse range of social phenomena. BA model assumes that nodes with more links (i.e., “popular nodes”) are more likely to be connected when new nodes entered a system. However, significant deviations from BA model have been reported in many social networks. Although numerous variants of BA model are developed, they still share the key assumption that nodes with more links were more likely to be connected. I think this line of research is problematic since it assumes all nodes possess the same preference and overlooks the potential impacts of agent heterogeneity on network formation. When joining a real social network, people are not only driven by instrumental calculation of connecting with the popular, but also motivated by intrinsic affection of joining the like. The impact of this mixed preferential attachment is particularly consequential on formation of social networks. I propose an integrative agent-based model of heterogeneous attachment encompassing both instrumental calculation and intrinsic similarity. Particularly, it emphasizes the way in which agent heterogeneity affects social network formation. This integrative approach can strongly advance our understanding about the formation of various networks.

Christian Vincenot Member since: Fri, Nov 13, 2020 at 03:42 AM Full Member

Master in Computer Science, Louis Pasteur University, Strasbourg, France, Ph.D. in Social Informatics, Kyoto University, Japan

Prof. Christian E. Vincenot is by nature an interdisciplinary researcher with broad scientific interests. He majored in Computer Science / Embedded Systems (i.e. IoT) at the Université Louis Pasteur (Strasbourg, France) while working professionally in the field of Computer Networking and Security. He then switched the focus of his work towards Computational Modelling, writing his doctoral dissertation on Hybrid Modelling in Ecology, and was awarded a PhD in Social Informatics by Kyoto University in 2011 under a scholarship by the Japanese Ministry of Research. He subsequently started a parallel line of research in Conservation Biology (esp. human-bat conflicts) under a postdoctoral fellowship of the Japanese Society for the Promotion of Science (JSPS) (2012-2014). This led him to create the Island Bat Research Group (, which he is still coordinating to this date. In 2014, he was appointed as the tenured Assistant Professor of the Biosphere Informatics Laboratory at Kyoto University. He also been occupying editorial roles for the journals PLOS ONE, Frontiers in Environmental Science, and Biology. In 2020, he created Ariana Technologies (, a start-up operating in the field of Data Science/Simulation and IoT for crisis management.

Prof. Vincenot’s main research interests lie in the theoretical development of Hybrid Mechanistic Simulation approaches based on Individual/Agent-Based Modeling and System Dynamics, and in their applications to a broad range of systems, with particular focus on Ecology.

Volker Grimm Member since: Wed, Jul 18, 2007 at 11:13 AM Full Member Reviewer

Volker Grimm currently works at the Department of Ecological Modelling, Helmholtz-Zentrum für Umweltforschung. Volker does research in ecology and biodiversity research.

How to model it: Ecological models, in particular simulation models, often seem to be formulated ad hoc and only poorly analysed. I am therefore interested in strategies and methods for making ecological modelling more coherent and efficient. The ultimate aim is to develop preditive models that provide mechanstic understanding of ecological systems and that are transparent and structurally realistic enough to support environmental decision making.

Pattern-oriented modelling: This is a general strategy of using multiple patterns observed in real systems as multiple criteria for chosing model structure, selecting among alternative submodels, and inversely determining entire sets of unknown model parameters.

Individual-based and agent-based modelling: For many, if not most, ecological questions individual-level aspects can be decisive for explaining system-level behavior. IBM/ABMs allow to represent individual heterogeneity, local interactions, and/or adaptive behaviour

Ecological theory and concepts: I am particularly interested in exploring stability properties like resilience and persistence.

Modelling for ecological applications: Pattern-oriented modelling allows to develop structurally realistic models, which can be used to support decision making and the management of biodiversity and natural resources. Currently, I am involved in the EU project CREAM, where a suite of population models is developed for pesticide risk assessment.

Standards for model communication and formulation: In 2006, we published a general protocol for describing individual- and agent-based models, called the ODD protocol (Overview, Design concepts, details). ODD turned out to be more useful (and needed) than we expected.

Raquel Guimarães Member since: Mon, Oct 21, 2019 at 09:27 AM Full Member

Ph.D., Demography, Universidade Federal de Minas Gerais, M.A., International and Comparative Education, Stanford University

Raquel Guimaraes is a Postdoctoral Research Scholar at IIASA with support from the Brazilian Coordination for the Improvement of Higher Education Personnel (CAPES). She is hosted by the Advanced Systems Analysis (ASA), Risk and Vulnerability (RISK), and World Population (POP) programs. Dr. Guimaraes is currently on sabbatical leave from her appointment as an Adjunct Professor in the Economics Department at the Federal University of Paraná (Brazil), where she carries out research on, as well as teaching, economic demography, development microeconomics and applied microeconometrics.

In her research at IIASA, Dr. Guimaraes aims to contribute to the extant literature and to policy-making by offering a case study from Brazil, examining whether and how individual exposure to floods did or not induce affected migration in a setting with intense urbanization, the city of Governador Valadares, in the State of Minas Gerais. To elucidate the role of vulnerability at the household-level in mediating the relationship between mobility and floods, she will rely on causal models and simulation analysis. Her study is aligned with and will have support from, the Brazilian Network for Research on Global Climate Change (Rede Clima), which is an important pillar in support of R&D activities of the Brazilian National Climate Change Plan.

Dr. Guimaraes graduated from the Federal University of Minas Gerais, Brazil, in 2007 with degrees in economics. She completed an MA degree in International Comparative Education at Stanford University (2011) and earned a doctorate in demography from the Federal University of Minas Gerais in 2014.

Jean-Pierre Müller Member since: Thu, Mar 30, 2023 at 08:50 AM Full Member

Ph.D., Computer science, Institut National Polytechnique de Grenoble, France., HDR, Université de Montpellier, France.

1987-1989: assistant professor at the Neuchâtel University (Switzerland)
1990-2001: full professor at the Neuchâtel University (Switzerland): artificial intelligence & software engineering
2001- : senior researcher at CIRAD in the unit “Gestion des Ressources et Environnement” (GREEN) and from 2021 “Savoirs ENvironnement Sociétés” (UMR SENS)

Former professor at the University of Neuchatel in Switzerland and now senior researcher at CIRAD in France, I am doing research on artificial intelligence since 1984. Having begun with logic programming, I naturally applied logics and its extensions (i.e. modal logics of various sorts) to specify agent behaviour. Since 1987, I moved both to embedded intelligence (using mobile robots) and multi-agent systems applied, in particular, to job-shop scheduling and complex system simulation and design. Since 2001, I exclusively work on modelling and simulation of socio-ecosystems in a multidisciplinary team on renewable resources management (GREEN). I am focusing on modelling complex systems in a multi-disciplinary (economist, agronomist, sociologists, geographers, etc.) and multi-actor (stakeholders, decision makers) setting. It includes:
- representing multiple points of view at various scales and levels on a complex socio-ecosystem, using ontologies and contexts
- representing the dynamics of such systems in a variety of formalisms (differential equations, automata, rule-based systems, cognitive models, etc.)
- mapping these representations into a simulation formalism (an extension of DEVS) for running experiments and prospective analysis.
This research is instantiated within a modelling and simulation platform called MIMOSA ( The current applications are the assessment of the sustainability of management transfer to local communities of the renewable ressources and the dynamics of agro-biodidversity through networked exchanges.

Enver Miguel Oruro Puma Member since: Tue, Mar 23, 2010 at 11:09 PM Full Member Reviewer

BA Psychology
(Cover simulation using NetLogo, January 2020)
Enver Miguel Oruro, Grace V.E. Pardo, Aldo B. Lucion, Maria Elisa Calcagnotto and Marco A. P. Idiart. Maturation of pyramidal cells in anterior piriform cortex may be sufficient to explain the end of early olfactory learning in rats. Learn. Mem. 2020. 27: 20-32 © 2020 Oruro et al.; Published by Cold Spring Harbor Laboratory Press
(paper using NetLogo, December 2020)
Enver Miguel Oruro, Grace V.E. Pardo, Aldo B. Lucion, Maria Elisa Calcagnotto and Marco A. P. Idiart. The maturational characteristics of the GABA input in the anterior piriform cortex may also contribute to the rapid learning of the maternal odor during the sensitive period Learn. Mem. 2020. 27: 493-502 © 2020 Oruro et al.; Published by Cold Spring Harbor Laboratory Press

Enver Oruro, BA Psych. PhD(s).
Computational Psychologist
[email protected]
Neurocomputational and Language Processing Laboratory, Institute of Physics/ UFRGS
Neurophysiology and Neurochemistry of Neuronal Excitability and Synaptic Plasticity Laboratory, Department of Biochemistry/ UFRGS

Meeting Organization

2009 First Meeting on Complex Systems -Neuroscience and Behavior Laboratory, School of Medicine UPCH Lima

2010 Second Meeting on Complex Systems - College of Psychologists of Peru / Colegio de Psicólogos del Perú (CPsP) Lima

2012 3rd Meeting on Complex Systems – Computational Social Psychology, /Neuroscience and Behavior Laboratory, School of Medicine UPCH Lima February 2012
2012 4th Meeting on Complex Systems – Cognotecnology and Cognitive Science, Neuroscience and Behavior Laboratory, School of Medicine UPCH Lima July 2012

2014 5th Meeting on Complex Systems – Complexity Roadmap. The Imperial City of the Incas, Cusco, April.

2015 Chair of “e-session on Neuroscience and Behavior” UNESCO UniTwin CS-DC’15
2015 Chair of “e-session on Social Psychology” UNESCO UniTwin CS-DC’15
CS-DC’15 (Complex Systems Digital Campus ’15 – World e-Conference) is organizing the e-satellites of CCS’15, the international Conference on Complex Systems. It is devoted to all scientists involved in the transdisciplinary challenges of complex systems, crossing theoretical questions with experimental observations of multi-level dynamics. CCS’15 is organized by the brand new ASU-SFI Center for Biosocial Complex Systems. Arizona State University, (USA) from Sept 28 to Oct 2, 2015, in close collaboration with the Complex Systems Society and the Santa Fe Institute. from

2018 Seminar in “Mother-Infant Attachment and Supercomputing”, NY. USA and Porto Alegre, Brazil, August 09.

2019 Seminar in Experimental and Computational Studies on Mother-Infant Relationship October 8 and 15, 2019 ICBS, /Determine the neural pathways by which the nervous system of the neonates establish attachment with their mothers is a problem that has motivated hypothesis and experiments at several scale levels, from neurotransmission to ethological level. UFRGS, Porto Alegre, Brazil.

2020 Seminar in Maternal Infant Relationship Studies: Neuroscience and Artificial Intelligence March 7 and 9
Goals 1. Discuss a Roadmap for mother-Infant relationship research in the framework of the UNESCO Complex System Digital Campus project.

Linea de investigacion: Estrategias de modelamiento en Psicobiologia y Psicologia Social
/ Linea estrategica 1: bases biologicas de la cognicion social desde sistemas complejos

David Earnest Member since: Sat, Mar 13, 2010 at 03:46 PM Full Member Reviewer

Ph.D. in political science (2004), M.A. in security policy studies (1994)

Two themes unite my research: a commitment to methodological creativity and innovation as expressed in my work with computational social sciences, and an interest in the political economy of “globalization,” particularly its implications for the ontological claims of international relations theory.

I have demonstrated how the methods of computational social sciences can model bargaining and social choice problems for which traditional game theory has found only indeterminate and multiple equilibria. My June 2008 article in International Studies Quarterly (“Coordination in Large Numbers,” vol. 52, no. 2) illustrates that, contrary to the expectation of collective action theory, large groups may enjoy informational advantages that allow players with incomplete information to solve difficult three-choice coordination games. I extend this analysis in my 2009 paper at the International Studies Association annual convention, in which I apply ideas from evolutionary game theory to model learning processes among players faced with coordination and commitment problems. Currently I am extending this research to include social network theory as a means of modeling explicitly the patterns of interaction in large-n (i.e. greater than two) player coordination and cooperation games. I argue in my paper at the 2009 American Political Science Association annual convention that computational social science—the synthesis of agent-based modeling, social network analysis and evolutionary game theory—empowers scholars to analyze a broad range of previously indeterminate bargaining problems. I also argue this synthesis gives researchers purchase on two of the central debates in international political economy scholarship. By modeling explicitly processes of preference formation, computational social science moves beyond the rational actor model and endogenizes the processes of learning that constructivists have identified as essential to understanding change in the international system. This focus on the micro foundations of international political economy in turn allows researchers to understand how social structural features emerge and constrain actor choices. Computational social science thus allows IPE to formalize and generalize our understandings of mutual constitution and systemic change, an observation that explains the paradoxical interest of constructivists like Ian Lustick and Matthew Hoffmann in the formal methods of computational social science. Currently I am writing a manuscript that develops these ideas and applies them to several challenges of globalization: developing institutions to manage common pool resources; reforming capital adequacy standards for banks; and understanding cascading failures in global networks.

While computational social science increasingly informs my research, I have also contributed to debates about the epistemological claims of computational social science. My chapter with James N. Rosenau in Complexity in World Politics (ed. by Neil E. Harrison, SUNY Press 2006) argues that agent-based modeling suffers from underdeveloped and hidden epistemological and ontological commitments. On a more light-hearted note, my article in PS: Political Science and Politics (“Clocks, Not Dartboards,” vol. 39, no. 3, July 2006) discusses problems with pseudo-random number generators and illustrates how they can surprise unsuspecting teachers and researchers.

Displaying 10 of 71 results system clear

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.