Community

Omar Guerrero Member since: Friday, January 30, 2015

PhD

My interests lie in the intersection of economics, networks, and computation. I am currently studying labour dynamics as a process where people flow throughout the economy by moving from one firm to another. I study these flows by looking at detailed data about employment histories of each individual and every firm in entire economies. Using this information, I construct networks of firms in order to map the roads that people take throughout their careers. This allows to study labour markets at an unprecedented fine-grained level of detail. I employ agent-based computing methods to understand how economic shocks and policies alter labour flows, which eventually translate into unemployment and other related problems.

Simon Johanning Member since: Monday, July 17, 2017

BMus Composition & Music Technology, MA DDC: Music Technology

IRPact - An integrated agent based modeling approach in innovation diffusion

Goal: The goal of IRPact is to develop a flexible and generic innovation-diffusion ABM (agent-based modelling) framework, based on requirements derived from a literature analysis. The aim of IRPact is to allow for modeling a large number of application contexts and questions of interest.
It provides a formal model (framework) as well as a software implementation in order to assist modelers with a basic infrastructure for their own research.
Conceptually it is thought to be part of the IRPsim (https://irpsim.uni-leipzig.de), with the vision to bring together rational approaches and cognitive modeling in an integrated approach within the context of sustainable energy markets.

Fabian Kostadinov Member since: Monday, April 15, 2013

MSc in Computer Science

Development of dynamic, adaptive, complex models of financial markets.

Geerten Hengeveld Member since: Thursday, January 24, 2019 Full Member

Wageningen University & Research
Currently researcher modelling at Biometris, Wageningen University & Research

modelling,
ecology, foraging, forestry, forest management, water management
scenario analysis
agent based modelling
individual based modelling
model quality, model evaluation, model governance

Leopoldo Sanchez-Cantu Member since: Friday, June 05, 2015

MD, MSc

Financial markets structure and behavior
Characterization of price fluctuations

Reinier Van Der Veen Member since: Wednesday, August 26, 2015

MSc., PhD

Researcher in sustainable production and consumption, the service economy, energy markets, and electricity balancing mechanisms.

Robert Axtell Member since: Thursday, July 14, 2016

Ph.D.

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

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.

Simone Righi Member since: Friday, June 08, 2018

I received a Ph.D. in Economics at the University of Namur (Belgium) in June 2012 with a thesis titled “Essays in Information Aggregation and Political Economics”.
After two years at the Research Center for Educational and Network Studies (Recens) of the Hungarian Academy of Sciences, I joined the Department of Economics “Marco Biagi” of the University of Modena and Reggio Emilia in January 2015 and then the Department of Agricultural and Food Sciences of the University of Bologna.
I am currently a Lecturer in Financial Computing at the Department Computer Science (Financial Computing and Analytics group) - University College London. Moreover I am an affiliated researcher of the DYNAMETS - Dynamic Systems Analysis for Economic Theory and Society research group and an affiliate member of the Namur Center for Complex Systems (Naxys).

My research interests concern the computational study of financial markets (microstructure, systemic properties and behavioral bias), of social Interactions on complex networks (theory and experiments), the evolution of cooperation in networks (theory and experiments) and the study of companies strategies in the digital economy.

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