Community

John Bradford Member since: Tuesday, November 04, 2014

Ph.D. Sociology, University of Tennessee

Currently working on agent-based modeling of wealth and income distributions; formalizing some of Luhmann’s theories of communication; modeling social norms; and modeling generative mechanisms of status hierarchies.

Audrey Lustig Member since: Thursday, July 18, 2013

PhD Candidate - Ecological Modelling and complex system - Lincoln University, New Zealand, Master's in computer science and modelling complex systems - ENS Lyon, France, Bioinformatics and Modeling Engineering - INSA Lyon, France

I am strongly interested in ecological modeling and complex system and truly enjoyed working with a variety of tools to uncover patterns in empirical data and explore their ecological and evolutionary consequences. My primary research is to conduct research in the field of ‘ecological complexity’, including the development of appropriate descriptive measure to quantify the structural, spatial and temporal complexity of ecosystem and the identification of the mechanism that generate this complexity, through modeling and field studies.
Currently investigated is how biological characteristics of invasive species (dispersal strategies and demographic processes) interact with abiotic variables and resource distribution to determine establishment success and spread in a complex heterogeneous environment (Individual based modelling integrated with GIS technologies).

Nanda Wijermans Member since: Monday, October 11, 2010 Full Member Reviewer

In my research I focus on understanding human behaviour in group(s) as a part of a complex (social) system. My research can be characterised by the overall question: ‘How does group or collective behaviour arise or change given its social and physical context?‘ More specifically, I have engaged with: ‘How is (individual) human behaviour affected by being in a crowd?’, ‘Why do some groups (cooperatively) use their resources sustainably, whereas others do not?‘, ‘What is the role of (often implicit simplistic) assumptions regarding human behaviour for science and/or management?’

To address these questions, I use computational simulations to integrate and reflect synthesised knowledge from literature, empirics and experts. Models, simulation and data analysis are my tools for gaining a deeper understanding of the mechanisms underlying such systems. More specifically, I work with agent-based modelling (ABM), simulation experiments and data analysis of large datasets. Apart from crowd modelling and social-ecological modelling, I also develop methodological tools to analyse social simulation data and combining ABM with other methods, such as behavioural experiments.

Jordi Sabater-Mir Member since: Tuesday, November 07, 2017

PhD in Artificial Intelligence

My research is focused on autonomous agents and multiagent systems. Specifically: Trust and reputation models, cognitive architectures, cognitive models and social simulation.

Xiaotian Wang Member since: Friday, March 28, 2014

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.

Calvin Pritchard Member since: Monday, May 16, 2016 Full Member Reviewer

Bachelor of Environment (Joint Honours Economics and Planning), University of Waterloo, Master of Arts (Economics), Queen's University

I am a developer for CoMSES Net as part of the Global Biosocial Complexity Initiative at Arizona State University. I work on improving model reuse, accessibility and discoverability through the development of the comses.net website and the CoMSES bibliographic database (catalog.comses.net). I also provide data analysis and software development advice on coupling models, version control, dependency management and data analysis to researchers and modelers.

My interests include model componentization, statistics, data analysis and improving model development and resuability practices.

Gudrun Wallentin Member since: Friday, October 28, 2016 Full Member

MSc. in GIS, Mag. in Ecology

Positions held today:
• Associate Professor for Geoinformatics and Ecology at the University of Salzburg (since 2017)
• UNIGIS Program Director (since 2020)
• Head of the Research Group “Spatial Simulation” (since 2013)

Major academic milestones:
• Assistant Professor, Department for Geoinformatics, University of Salzburg (2013-2017)
• Associate Faculty in the FWF Doctoral College “GIScience” (2013-2017)
• Director of Studies UNIGIS MSc distance learning programs, University of Salzburg (2012-2020)
• PhD at the University of Innsbruck on ecological modelling (2011)
• Research Assistant Austrian Academy of Sciences, GIScience Institute (2007-2011)
• Magistra in Ecology, Univ. of Innsbruck (2001) and MSc in GIS, Univ. of Edinburgh (2006)

Spatially-explicit simulation modelling of complex, ecological systems: * the added value of spatially-explicit modelling * Hybrid agent-based and system-dynamics modelling in ecology * Agent-based models, Cellular Automata

Salma Alsassa Member since: Thursday, August 24, 2017

PhD student

modeling infection system using agent-based modeling

Tika Adhikari Member since: Friday, January 20, 2012 Full Member Reviewer

Ph D, Student

Development of spatial agent-based models to sustainability science and ecosystem service assessment, integration of agent-based model with biophysical process based model, improvement of theory of GIScience and land use change science, development of spatial analytical approach (all varieties of spatial regression), spatial data modeling including data mining, linking processes such as climate change, market, and policy to study patterns.

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