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Elizabeth Hunter received a BA in Mathematics and Economics at Boston University in 2011. She worked as a health economics researcher at Research Triangle Institute for three years where she worked on a team that developed the risk adjustment models for the US health insurance exchanges. She attended the University of Limerick and received an MSc in Mathematical Modelling in 2015. She completed a PhD at Technological University Dublin. Her PhD research focuses on agent-based simulations for infectious disease epidemiology with the goal of creating an agent-based simulation of Ireland. Elizabeth is currently working on the Precise4Q as a Postdoctoral researcher working on predictive modelling in stroke.
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.
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:
Research fellow, PhD Candidate (University of Kassel)
Energy system transiton modelling
* stakeholder and market modelling, governance and policy modelling,
* agent-based modelling (ABM), optimisation,
* model coupling, open and integrative modelling framework,
* open source, S4F
social-ecological modelling; cognitive modelling; agent-based modeling&simulation; data science; smart city modelling; artificial intelligence; large-scale simulation
Agent-based modelling
Modal choice simulation
Multi-agent system
Behavioural theory
My research is focused on understanding the importance of spatial and temporal environmental variability on communities and populations. The key question I aim to address is how the anthropogenic impacts, such as disturbances of individual animals or changed landscape heterogeneity associated with climate changes, influence the persistence of species. The harbour porpoise is an example of a species that is influenced by anthropogenic disturbances, and much of my research has focused on how the Danish porpoise populations are influenced by noise from offshore constructions. I use a wide range of modelling tools to assess the relative importance of different sources of environmental variation, including individual-based/agent based models, spatial statistics, and classical population models. This involves development of computer programs in R and NetLogo. In addition to my own research I currently supervise three PhD students and participate in the management of Department of Bioscience at Aarhus University.
Amineh Ghorbani is an assistant professor at the Engineering Systems and Services Department, Delft University of Technology, the Netherlands. She is also an affiliated member of the “Institutions for Collective Action” at Utrecht University. She obtained her M.Sc. in Computer Science (Artificial intelligence) from University of Tehran (Iran) (2009, honours) and her PhD from Delft University of Technology (2013, cum laude).
During her PhD, Amineh developed a meta-model for agent-based modelling, called MAIA, which describes various concepts and relations in a socio-technical system. This modelling perspective helped her develop a modelling paradigm that she refers to as institutional modelling.
Her current area of research is understanding the emergence and dynamics of institutions (set of rule organizing human society) using modelling. She is interested in how bottom-up collective action emerges and how institutions emergence and change within communities.
collective action
institutional emergence
evolution of institutions
community energy systems
I live in Salento, a small land located between two seas in Southeastern Italy. I work as an educator in an adult school. My educational background includes a degree in Life Sciences. During my post-graduate training, I was involved in researching the genetic and molecular responses of cells to environmental and genomic stresses. Currently, I am interested in exploring theoretical biology and complex adaptive systems through agent-based modelling.
Artificial Life, Adaptive Cognition, Evolvability
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