Community

Furkan Gürsoy Member since: Thursday, August 02, 2018 Full Member

Ph.D., Management Information Systems, Boğaziçi University, M.Sc., Data Science, Istanbul Şehir University, B.Sc., Management Information Systems, Boğaziçi University

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.

Uzair Ahmad Member since: Thursday, February 26, 2015

PhD, MIT

Complex Adaptive Systems, Data Analytics and Visualization

Marta Czarnocka-Cieciura Member since: Wednesday, January 08, 2020

I graduated Bachelor and Master studies at the University of Warsaw, obtaining the diploma in biology at College of Inter-Faculty Individual Studies in Mathematics and Natural Sciences (MISMaP). After graduation I worked as a freelancer in data science and statistics, then worked for 2 years as a data scientist in an IT startup and now I am working as a statistician in The Polish National Information Processing Institute (OPI PIB) in a group analysing condition of science and higher education in Poland. My interests: agent based modelling, evolutionary ecology, statistics, data science, sociology of science.

Thomas Clemen Member since: Tuesday, September 17, 2019 Full Member

Diploma in Computer Science, Technical University of Dortmund, Germany, Dr. rer. nat. in Computer Science, Christian-Albrechts University, Kiel, Germany

social-ecological modelling; cognitive modelling; agent-based modeling&simulation; data science; smart city modelling; artificial intelligence; large-scale simulation

Down Networks Member since: Monday, October 26, 2015

Down Networks is a real time, progressively agile non profit startup whose goals are to fund its research via pragmatically aggressive altruistic entrepreneurial pursuits informed by proprietary in-house techniques, open source technology and refined scientific methodology.

Claudine Gravel-Miguel Member since: Thursday, November 01, 2012 Full Member Reviewer

M.A., Anthropology, University of Victoria, Ph.D., Anthropology, Arizona State University

Dr. Gravel-Miguel currently works as a Postdoctoral Research Scholar for the Institute of Human Origins at Arizona State University. She does research in Archaeology and focuses on the Upper Paleolithic of Southwest Europe. She currently works on projects ranging from cultural transmission to human-environment interactions in prehistory.

Archaeology, GIS, ABM, social networks, portable art, ornaments, data science

Tom Briggs Member since: Tuesday, December 13, 2016 Full Member Reviewer

MPS, Industrial/Organizational Psychology, BA, Psychology

PhD Student, Computational Social Science
Department of Computational and Data Sciences
George Mason University
Fairfax, VA, USA

I use ABM to study organizations, leadership, employee behavior and performance, and the social/psychological theories addressing workplace behavior and outcomes.

I have also used ABM to explore mass violence, active shooters, and mass shootings, including the spread of mass violence and its antecedents.

Andrew Crooks Member since: Monday, February 09, 2009 Full Member

Andrew Crooks is an Associate Professor with a joint appointment between the Computational Social Science Program within the Department of Computational and Data Sciences and the Department of Geography and GeoInformation Science, which are part of the College of Science at George Mason University. His areas of expertise specifically relate to integrating agent-based modeling (ABM) and geographic information systems (GIS) to explore human behavior. Moreover, his research focuses on exploring and understanding the natural and socio-economic environments specifically urban areas using GIS, spatial analysis, social network analysis (SNA), Web 2.0 technologies and ABM methodologies.

GIS, Agent-based modeling, social network analysis

Christopher Parrett Member since: Sunday, October 20, 2019 Full Member

I am a lowly civil servant moonlighting as a PhD student interested in urban informatics, Smart Cities, artificial intelligence/machine learning, all-things geospatial and temporal, advanced technologies, agent-based modeling, and social complexity… and enthusiastically trying to find a combination thereof to form a disseration. Oh… and I would like to win the lottery.

  • Applied data science (machine/deep learning applications) and computational modeling (agent-based
    modeling) in U.S. Government
  • Geographic Information Systems and analysis of dense urban environments and complex terrain
  • Complexity theory and computational organizational design of distributed enterprise teams.
  • Human Capital Management and Talent Management policy development

Allen Lee Member since: Thursday, May 10, 2007 Full Member Reviewer

MSc Computer Science and Informatics, Indiana University - Bloomington, BSc Computer Science, Indiana University - Bloomington

I am a full stack software engineer who has been building cyberinfrastructure for computational social science at Arizona State University since 2006; projects include the Digital Archaeological Record, the Virtual Commons, the Social Ecological Systems Library, Synthesizing Knowledge of Past Environments (SKOPE), the Port of Mars, and CoMSES Net, where I serve as co-director and technical lead.

I also work to improve the state of open, transparent, reusable, and reproducible computational science as a Carpentries certified instructor and maintainer for the Python Novice Gapminder lesson, and member of the Force 11 Software Citation Implementation Working Group and Consortium of Scientific Software Registries and Repositories.

My research interests include collective action, social ecological systems, large-scale software systems engineering, model componentization and coupling, and finding effective ways to promote and facilitate good software engineering practices for reusable, reproducible, and interoperable scientific computation.

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