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ABM of financial markets, focused on systemic risk.
Ecological modelling
Social Ecnomic/ecological complexity
My primary research interests lie at the intersection of two fields: evolutionary computation and multi-agent systems. I am specifically interested in how evolutionary search algorithms can be used to help people understand and analyze agent-based models of complex systems (e.g., flocking birds, traffic jams, or how information diffuses across social networks). My secondary research interests broadly span the areas of artificial life, multi-agent robotics, cognitive/learning science, design of multi-agent modeling environments. I enjoy interdisciplinary research, and in pursuit of the aforementioned topics, I have been involved in application areas from archeology to zoology, from linguistics to marketing, and from urban growth patterns to materials science. I am also very interested in creative approaches to computer science and complex systems education, and have published work on the use of multi-agent simulation as a vehicle for introducing students to computer science.
It is my philosophy that theoretical research should be inspired by real-world problems, and conversely, that theoretical results should inform and enhance practice in the field. Accordingly, I view tool building as a vital practice that is complementary to theoretical and methodological research. Throughout my own work I have contributed to the research community by developing several practical software tools, including BehaviorSearch (http://www.behaviorsearch.org/)
I obtained a PhD in database information theory from the University of the West of Scotland in 2015, and have been a researcher at the James Hutton Institute ever since. My areas of research are agent-based-modelling (ABM), data curation, effective use of infrastructure as a service (IaaS), and semantic information representation and extraction using formal structures such as computerised ontologies, relational databases and any other structured or semi-structured data representations. I primarily deal with social and agricultural models and was originally taken on in the role of knowledge engineer in order to create the ontology for the H2020 project, Green Lifestyles, Alternative Models and Upscaling Regional Sustainability (GLAMURS). Subsequent work, for the Scottish Government has involved the use of IaaS, more commonly referred to as the “cloud” to create rapidly deployable and cheap alternatives to in-house high-performance computing for both ABM and Geographical Information System models.
It is the mixture of skills and interests involving modelling, data organisation and computing infrastructure expertise that I believe will be highly apposite in the duties associated with being a member of the CoMSES executive. Moreover, prior to joining academia, I spent about 25 years as a developer in commercial IT, in the agricultural, entertainment and banking sectors, and feel that such practical experience can only benefit the CoMSES network.
Match-making platforms for sociocultural change.
About me
Name: Dr. Julia Kasmire
Position: Post-doctoral Research Fellow
Where: UK Data Services and Cathie Marsh Institute at the University of Manchester.
Short Bio
2004 - BA in Linguistics from the University of California in Santa Cruz, including college honours, departmental honours and one year of study at the University of Barcelona.
2008 - MSc in the Evolution of Language and Cognition from the University of Edinburgh, with a thesis on the effects of various common simulated population features used when modelling language learning agents.
2015 - PhD from Faculty of Technology, Policy and Management at the Delft University of Technology under the supervision of Prof. dr. ig. Margot Wijnen, Prof. dr. ig. Gerard P.J. Dijkema, and Dr. ig. Igor Nikolic. My PhD thesis and propositions can be found online, as are my publications and PhD research projects (most of which addressed how to study transitions to sustainability in the Dutch horticultural sector from a computational social science and complex adaptive systems perspective).
Additional Resources
Many of the NetLogo models I that built or used can be found here on my CoMSES/OpenABM pages.
My ResearchGate profile and my Academia.org profile provide additional context and outputs of my work, including some data sets, analytical resources and research skills endorsements.
My LinkedIn profile contains additional insights into my education and experience as well as skills and knowledge endorsements.
I try to use Twitter to share what is happening with my research and to keep abreast of interesting discussions on complexity, chaos, artificial intelligence, evolution and some other research topics of interest.
You can find my SCOPUS profile and my ORCID profile as well.
Complex adaptive systems, sustainability, evolution, computational social science, data science, empirical computer science, industrial regeneration, artificial intelligence
I am a Research Associate with an interdisciplinary background spanning economics, social sciences, and international relations. After several years of professional experience outside academia, I now focus on applying agent-based modeling to management control challenges. My research explores how organizations can mitigate dysfunctional behaviors such as lying, fraud, and other forms of opportunism, aiming to design control systems that balance the pursuit of organizational goals while maintaining individual and organizational integrity.
Adapting Agents on Evolving Networks: An evolutionary game theory approach
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Displaying 10 of 400 results for "J Van Der Beek" clear search