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I am a computational archaeologist interested in how individuals and groups respond to both large scale processes such as climate change and local processes such as violence and wealth inequality. I am currently a PhD Candidate in the Department of Anthropology at Washington State University.
My dissertation research focuses on experimenting with paleoecological data (e.g., pollen) to assess whether or not different approaches are feasible for paleoclimatic field reconstructions. In addition, I will also use pollen data to generate vegetation (biome) reconstructions. By using tree-ring and pollen data, we can gain a better understanding of the paleoclimate and the spatial distribution of vegetation communities and how those changed over time. These data can be used to better understand changes in demography and how people responded to environmental change.
In Summer 2019, I attended the Santa Fe Institute’s Complex Systems Summer School, where I got to work in a highly collaborative and interdisciplinary international scientific community. For one of my projects, I got to merry my love of Sci-fi with complexity and agent-based modeling. Sci-fi agent-based modeling is an anthology and we wanted to build a community of collaborators for exploring sci-fi worlds. We also have an Instagram page (@Scifiabm).
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
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.
Agent-based modelling
Modal choice simulation
Multi-agent system
Behavioural theory
social-ecological modelling; cognitive modelling; agent-based modeling&simulation; data science; smart city modelling; artificial intelligence; large-scale simulation
Arpan Jani received his PhD in Business Administration from the University of Minnesota in 2005. He is currently an Associate Professor in the Department of Computer Science and Information Systems at the University of Wisconsin – River Falls. His current research interests include agent-based modeling, information systems and decision support, behavioral ethics, and judgment & decision making under conditions of risk and uncertainty.
agent-based modeling; behavioral ethics; information systems and decision support; project management; judgment & decision making under conditions of risk and uncertainty.
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
I´m a full Professor at the Universidad Autónoma de Baja California in Mexico. I teach computer sciences and software engineering in graduate and undergraduate academic programs.
I am a lowly civil servant moonlighting as a PhD student interested in urban informatics, Smart Cities, artificial intelligence/machine learning, all-things geospatial and temporal, advanced technologies, agent-based modeling, and social complexity… and enthusiastically trying to find a combination thereof to form a disseration. Oh… and I would like to win the lottery.
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:
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