To understand the nature of sustainable biophysical/economic systems. To determine the necessary and sufficient conditions for sustainability. To explore the trade-off between sustainability and social or economic justice. To investigate the application of the MEP and/or the MEPP to economic systems, or agent-based models of economic systems.

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.

Secondary education, agent-based modeling and computational science in education

Social Simulation using MABS. At present, research to expand SocLab in order to model emotions and morality.
Others: Organisations, Soft Systems, Planning methodologies.

My main research field is health economic modeling with the main focus on sexually transmitted diseases. We are trying to build a agent-based model using the FLAME-framework (www.flame.ac.uk).

My dissertation research at the Johnson-Shoyama Graduate School of Public Policy focuses on food safety and consumer choices, using agent-based models as a novel method for investigating this policy space.

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.

• the link between economic exchange, solidarity, and inter-group conflict
• peer-review evaluation in scientific publishing
• integrating Agent-Based Modelling (ABM) with Social Network Analysis (SNA)