Emilie Lindkvist Member since: Friday, March 03, 2017 Full Member


I have a backround in computer science, worked in natural resource management, and ended up with a PhD in Sustainability Sciences!

My interests are to explore aspects of sustainability, resilience, and adaptive management in social-ecological systems using agent-based models and other simulation models.

Paul Van Liedekerke Member since: Thursday, May 31, 2018

Interested in numerical models and new conceptual ideas, applications from industry to medicine.

I focus on numerical modeling of mechanics of solid materials and cell mechanics. The models that I developed so far address granular matters, bio-fluids, cellular tissues, and individual cells.

I further develop Agent-based Models, which are methods to predict collective behavior from individual dynamics controlled by rules or differential equations. Examples: tumor growth, swarms, crowd movement.

The methods I used are Particle-based methods which offer great flexibility within physical modeling, and can operate in a large range of scales, from atomistic scales (e.g. Molecular Dynamics) to continuum approaches (e.g. Smoothed Particle Hydrodynamics).

Robert Axtell Member since: Thursday, July 14, 2016


Agent-based computing in economics and finance
Large-scale agent-based models
Agent models calibrated by micro-data
Complex adaptive systems
Mathematical analysis of agent systems

Kenneth Aiello Member since: Thursday, January 23, 2020 Full Member

Ph.D., Biology and Society, Arizona State University, B.S., Sociology, Arizona State University,, B.S., Biology, Arizona State University

Kenneth D. Aiello is a postdoctoral research scholar with the Global BioSocial Complexity Initiative at ASU. Kenneth’s research contributes to cross disciplinary conversations on how historical developments in biological, social, and cultural knowledge systems are governed by processes that transform the structure, dynamics, and function of complex systems. Applying computational historical analysis and epistemology to question what scientific knowledge is and how we can analyze changes in knowledge, he uses text analysis, social network analysis, and machine learning to measure similarities and differences between the knowledge claims of individual agents and groups. His work builds on how to assess contested knowledge claims and measure the evolution of knowledge across complex systems and multiple dimensions of scale. This approach also engages in dynamic new debates about global and local structures of knowledge shaped by technological innovation within microbiology related to public policy, shrinking resources given to biomedical ideas as opposed to “translation”, and the ethics of scientific discovery. Using interdisciplinary methods for understanding historical content and context rich narratives contributes to understanding new domains and major transitions in science and provides a richer understanding of how knowledge emerges.

Nicholas Magliocca Member since: Wednesday, March 21, 2018 Full Member

My broad research interests are in human-environmental interactions and land-use change. Specifically, I am interested in how people make land-use decisions, how those decisions modify the functioning of natural systems, and how those modifications feedback on human well-being, livelihoods, and subsequent land-use decisions. All of my research begins with a complex systems background with the aim of understanding the dynamics of human-environment interactions and their consequences for environmental and economic sustainability. Agent-based modeling is my primary tool of choice to understand human-environment interactions, but I also frequently use other land change modeling approaches (e.g., cellular automata, system dynamics, econometrics), spatial statistics, and GIS. I also have expertise in synthesis methods (e.g., meta-analysis) for bringing together leveraging disparate forms of social and environmental data to understand how specific cases (i.e., local) of land-use change contribute to and/or differ from broader-scale (i.e. regional or global) patterns of human-environment interactions and land change outcomes.

Gert Hofstede Member since: Wednesday, March 05, 2014


My research focuses on using generic social science in creating models of social reality, in particular self-organization of social systems.

Murat Yildizoglu Member since: Friday, October 18, 2013 Full Member Reviewer

Ph.D. in economics, Strasbourg University

Analyzing economic dynamics through game theory and agent based evolutionary models. My research topics go from dynamics of organizations to industrial dynamics, macroeconomic dynamics and economic policy analysis.

María Del Castillo Member since: Tuesday, February 18, 2014


Archaeological Simulation of Social Interactions, mainly between hunter gatherers societies.

Enver Miguel Oruro Puma Member since: Tuesday, March 23, 2010 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

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