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I am an Associate Professor of Data Analytics at Trinity Business School, Trinity College Dublin, The University of Dublin and a Senior Fellow of the Higher Education Academy. I was the Director of Postgraduate Teaching at the Department of Management Science, Lancaster University Management School overseeing MSc programmes in Business Analytics, Management Science and Marketing Analytics, Logistics and Supply Chain Management, e-Business and Innovation, and Project Management.
My research interests lie in the areas of predictive analytics using simulation. I am particularly interested in simulation modelling methodology (symbiotic simulation, hybrid modelling, agent-based simulation, discrete-event simulation) with applications in operations and supply chain management (e.g. hospital, manufacturing, transportation, warehouse) and social dynamics (e.g. diffusion of perception). Currently, I am the associate editor of the Journal of Simulation and the secretary of The OR Society‘s Special Interest Group in Simulation. I am the track coordinator of Agent-Based Simulation for the Winter Simulation Conference 2018.
Interested in how technology innovation impacts people’s lives.
I am a FullStack Developer & GIS Specialist with a proven track record in developing GIS-driven software solutions, urban planning tools, and spatial analysis platforms. With expertise in technologies, I combine technical skills with leadership to deliver impactful projects that bridge technology and geospatial innovation.
Agent Based Modeing in geosimulation
GeoSimulation
GeoWeb
GeoAI
Social Innovation and Monetary Innovation. Developing Social Finance tools for social enterprises.
Creativity, Innovation, Participation, Collaboration
Dr. Morteza Mahmoudzadeh is an assitant professor at the University of Azad at Tabriz in the Department of Managent and the director of the Policy Modeling Research Lab. Dr. Mahmoudzadeh did a degree in Software Engineering and a PhD in System Sciences. Dr. Mahmoudzadeh currently works on different regional and national wide projects about modeling sustaiblity and resilience of industrial ecosystems, innovation networks and socio-environmental systems. He also works on hybrid models of opinion dynamics and agent based models specifically in the field of modeling customers behavior and developing managerial tools for strategic marketing policy testing. His team at Policy Modeling Research Lab. currently work on developing a web based tool with python for systems modeling using system dynamics, Messa framework for agent-based modeling and Social Networks Analysis.
Modeling Complex systems, Simulation: System Dynamics, Agent Based and Discrete Event
System and Complexity Theory
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.
structure of scientific revolutions, dynamics of innovation, exploration-exploitation dynamics
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