Community

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

Antonio Franco Member since: Wednesday, July 13, 2016

Master degree in Electrical Engineering

Eric Kameni Member since: Monday, October 19, 2015 Full Member Reviewer

Ph.D. (Computer Science) - Modelisation and Application, Institute for Computing and Information Sciences (iCIS) and Institute for Science, Innovation and Society (ISIS), Faculty of Science, Radboud University, Netherland, Master’s degree with Thesis, University of Yaounde I

Eric Kameni holds a Ph.D. in Computer Science option modeling and application from the Radboud University of Nijmegen in the Netherlands, after a Bachelor’s Degree in Computer Science in Application Development and a Diploma in Master’s degree with Thesis in Computer Science on “modeling the diffusion of trust in social networks” at the University of Yaoundé I in Cameroon. My doctoral thesis focused on developing a model-based development approach for designing ICT-based solutions to solve environmental problems (Natural Model based Design in Context (NMDC)).

The particular focus of the research is the development of a spatial and Agent-Based Model to capture the motivations underlying the decision making of the various actors towards the investments in the quality of land and institutions, or other aspects of land use change. Inductive models (GIS and statistical based) can extrapolate existing land use patterns in time but cannot include actors decisions, learning and responses to new phenomena, e.g. new crops or soil conservation techniques. Therefore, more deductive (‘theory-driven’) approaches need to be used to complement the inductive (‘data-driven’) methods for a full grip on transition processes. Agent-Based Modeling is suitable for this work, in view of the number and types of actors (farmer, sedentary and transhumant herders, gender, ethnicity, wealth, local and supra-local) involved in land use and management. NetLogo framework could be use to facilitate modeling because it portray some desirable characteristics (agent based and spatially explicit). The model develop should provide social and anthropological insights in how farmers work and learn.

E Larsen Member since: Wednesday, August 31, 2016

Masters degree in Sociology

Social inequality, ethnic segregation, computational sociology.

Manolis Tzouvelekas Member since: Sunday, November 02, 2014

B.A in Public Administration, European Masters Degree in Public Administration

Social Innovation and Monetary Innovation. Developing Social Finance tools for social enterprises.

Gayanga Herath Member since: Wednesday, March 14, 2018 Full Member

Master's degree in Information Technology, Management & Organisational Change at Lancaster University, Bachelor of Engineering (BEng) (Hons) in Computer Networks And Security at Staffordshire University, PhD in Organizational Cognition at University of Southern Denmark (Present)

An ambitious and driven individual with knowledge and project experience in computer networks and security (BEng (Hons)), along with a masters degree at a top 10 UK university in the domain of IT, management and organizational change with a distinction, and is currently working as a Ph.D. Research fellow in Denmark.

Current Ph.D. Project - Work Improvisation, looking into more flexible and plastic management through cognition.

Organizational Cognition
Organizational behaviour
Organizational change
Gamification
Fit
Recruitment & Selection
Distribted Cognition

Konstantinos Raptis Member since: Saturday, December 08, 2012

Master's degree, Information Management and Web Technologies, University of the Aegean, DipEng, Information and Communication Systems Engineering, University of the Aegean

Simen Oestmo Member since: Saturday, September 21, 2013

Bachelor degree in Social Sciences - Archaeology, Master of Arts in Anthropology - Archaeology, PhD in Anthropology - Archaeology

Sedar Olmez Member since: Wednesday, November 06, 2019 Full Member

MSci in Computer Science, MSc in Data Analytics and Society

Sedar is a PhD student at the University of Leeds, department of Geography. He graduated in Computer Science at King’s College London 2018. From a very early stage of his degree, he focused on artificial intelligence planning implementations on drones in a search and rescue domain, and this was his first formal attempt to study artificial intelligence. He participated in summer school at Boğaziçi University in Istanbul working on programming techniques to reduce execution time. During his final year, he concentrated on how argumentation theory with natural language processing can be used to optimise political influence. In the midst of completing his degree, he applied to Professor Alison Heppenstall’s research proposal focusing on data analytics and society, a joint endeavour with the Alan Turing Institute and the Economic and Social Research Council. From 2018 - 2023 he will be working on his PhD at the Alan Turing Institute and Leeds Institute for Data Analytics.

Sedar will be focusing on data analytics and smart cities, developing a programming library to try simulate how policies can impact a small world of autonomous intelligent agents to try deduce positive or negative impact in the long run. If the impact is positive and this is conveyed collectively taking into consideration the agent’s health, happiness and other social characteristics then the policy can be considered. Furthermore, he will work on agent based modelling to solve and provide faster solutions to economic and social elements of society, establishing applied and theoretical answers. Some other interests are:

  • Multi-agent systems
  • Intelligent agents
  • Natural language processing
  • Artificial intelligence planning
  • Machine learning
  • Neural networks
  • Genetic programming
  • Geocomputation
  • Argumentation theory
  • Smart cities

Francisco Rodes Member since: Wednesday, January 31, 2018

Bachelor's Degree in Industrial Engineering, Master's Degree in Industrial Engineering and Management

As a Master’s Thesis student, I am intended to apply Artificial Intelligence to an already existing model with the aim of making it more accurate.

Even though I do not have the focus point and the scope of the research clear yet, the road map is set to start from a very simple model to validate the technology and methodology used and then continue with more abitiuos projects.

I like the co-operation that I have found in this space and I think that I could both learn a lot from the community and add value with my novel trials and findings.

Of course I would be pleased to update the status of my project and I would try to help if I have the proper knowledge or different angle to other peers who seek for seconds opinions.

Thank you,
Francisco

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