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Eric is a Research Fellow in the Complexity programme at the MRC/CSO Social and Public Health Unit at the University of Glasgow, working on agent-based simulation approaches to complex public health issues. Prior to this he was a Research Lecturer/Senior Lecturer in Artificial Intelligence and Interactive Systems in the School of Computing at Teesside University. Before working at Teesside, he worked on the CLC Project at the University of Southampton, a multidisciplinary project which focuses on the application of complexity science approaches to the social science domain.
Eric received a BA with Honours in Psychology from Pennsylvania State University, and a PhD from the School of Computing at the University of Leeds. After his PhD, he worked as a JSPS Postdoctoral Research Fellow at the University of Tokyo, conducting research in computer simulation and robotics.
Gary Polhill did a degree in Artificial Intelligence and a PhD in Neural Networks before spending 18 months in industry as a professional programmer. Since 1997 he has been working at the Institute on agent-based modelling of human-natural systems, and has worked on various international and interdisciplinary projects using agent-based modelling to study agricultural systems, lifestyles, and transitions to more sustainable ways of living. In 2016, he was elected President of the European Social Simulation Association, and was The James Hutton Institute’s 2017 Science Challenge Leader on Developing Technical and Social Innovations that Support Sustainable and Resilient Communities.
Multi-agent Systems, Agent Based Modeling, Artificial Intelligence
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
Multi-agent systems, Cognitive Agent, GAMA
I am a PhD candidate in machine learning and cybersecurity, in the mean time I am also the laboratory director of the AI Testing Laboratory of CLR Labs where I work with a beautiful team of passionate and brilliant people on evaluating neural networks from robustness to system’s cybersecurity and explainability, I am based in the Marseille area, between sea, mountains and buildings.
I am a proud husband, father of one and son.
I study how deep models break and how to make them unbreakable — adversarial robustness, model security, and the geometry of learned representations applied to cyber threats.
I am a researcher in data science for sustainability, working at the intersection of society, politics, economy, and the environment. My work integrates statistics, artificial intelligence, and complex systems approaches to generate robust, data-driven evidence that supports decision-making in complex socio-environmental contexts.
My research focuses on understanding and modeling socio-ecological systems, with the goal of improving sustainability outcomes through interdisciplinary analysis and innovative analytical tools.
My research interests are organized around four main areas:
🌱 Socio-ecological systems dynamics
I study the interactions between human societies and ecosystems, with particular attention to the social, economic, and political processes that shape these dynamics.
💚 Nature’s values
I explore the diverse ways in which people value nature and work on integrating these perspectives into decision-making processes and public policy design.
🦋 Biodiversity management and conservation
I apply computer vision, statistical modeling, and spatial analysis to species classification and monitoring, generating evidence to support biodiversity management and conservation strategies.
🏛️ Governance and public policy
I analyze policy integration and coherence using quantitative and data-driven methods, aiming to improve policy design, implementation, and decision-making processes.
Overall, my research seeks to integrate interdisciplinary approaches to strengthen sustainability, generating knowledge and innovative tools based on data science and artificial intelligence that support both public policy development and the management and conservation of socio-ecological systems.
John E. McEneaney is Professor Emeritus of Learning and Teaching in the School of Education and Human Services at Oakland University, Rochester, MI, USA.
Learning theories, Language education, Literacy education, Artificial Intelligence, Computational modeling
Ifigeneia Koutiva (female) is a senior environmental engineer, holding a PhD in Civil Engineering (NTUA), a Postgrad Diploma in Water Resources and Environmental Management (Un. of Belgrade - e-learning), an MSc in Environmental Technology (Imperial College London) and an MSc in Mining and Metallurgy Engineering (NTUA). Her PhD was funded by the Greek Ministry of Education through Heracleitous II scholarship. She is currently a postdoctoral scholar of the State Scholarship Foundation (IKY) for 2020 - 2021. She has 10 years of experience in various EU funded research projects, both as a researcher and as a project manager, in the fields of socio-technical simulation, urban water modelling, modelling and assessment of alternative water technologies, artificial intelligence, social quantitative research, KPI and water indicators development and assessment and analysis of large data sets. She is very competent with programming for creating ICT tools for agent based modelling and data analysis tools and she is an experienced user of spatial analysis software and tools. She is also actively involved in the design and implementation of numerous consultation workshops and conferences. She has authored more than 20 scientific journal articles, conferences articles and research reports.
My research interests lay within the interface of social, water and modelling sciences. I have created tools that explore the effects of water demand management policies in domestic urban water demand behaviour and the effects of civil decision making in flood risk management. I am interested in agent based modelling, artificial intelligence techniques, the creation of ABM tools for civil society, Circular Economy, distributed water technologies and overall urban water management.
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