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Sr Machine Learning Engineer, Google Developer Expert in Cloud and Machine Learning. CompTIA Security+, AWS certified Machine Learning specialty.
Generative AI, LLMs, Multi-Agent Modeling, Agent-Based Modeling, Cellular Automata, Graph Networks, Deep Learning, Social Sciences
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.
I am currently Associate Professor of Organizational Cognition and Director of the Research Centre for Computational & Organisational Cognition at the Department of Language and Communication, University of Southern Denmark, Slagelse. My current research efforts are on socially-based decision making, agent-based modeling, cognitive processes in organizations and corporate social responsibility. He is author of more than 50 articles and book chapters, the monograph Extendable Rationality (2011), and he recently edited Agent-Based Simulation of Organizational Behavior with M. Neumann (2016).
My simulation research focuses on the applications of ABM to organizational behavior studies. I study socially-distributed decision making—i.e., the process of exploiting external resources in a social environment—and I work to develop its theoretical underpinnings in order to to test it. A second stream of research is on how group dynamics affect individual perceptions of social responsibility and on the definition and measurement of individual social responsibility (I-SR).
My general research interest is on modeling of complex natural and human systems systems. Specifically, I am interested in modeling agricultural production systems, that blends the complexity, multiplicity of scales and feedbacks of biophysical interactions in natural ecosystems with the additional intricacies of human decision-making. During last years I have coordinated the development and evaluation of an agent-based of agricultural production systems in the Argentinean Pampas.
Research focuses on the coupled dynamics of human and natural systems, specifically in the context of forest dynamics. I utilize a variety of modeling and analysis techniques, including agent-based modeling, cellular automata, machine learning and various spatial statistics and GIS-related methods. I am currently involved in projects that investigate the anthropogenic and biological drivers behind native and invasive forest pathogens and insects.
Tarik Hadzibeganovic is a complex systems researcher and cognitive scientist interested in all challenging topics of mathematical and computational modeling, in both basic and applied sciences. His particular focus has been on several open questions in evolutionary game theory, behavioral mathematical epidemiology, sociophysics, network theory, and episodic memory research. When addressing these questions, he combines mathematical, statistical, and agent-based modeling methods with laboratory behavioral experiments and Big Data analytics.
I am an environmental archaeologist, specializing in charcoal analysis, computational and analytical proxy modeling, and quantitative methods to understand the dynamic relationship between fire, humans, and long-term environmental change. I work primarily in the Western United States and the Western Mediterranean. I am passionate about our public lands and ensuring that everyone has access and opportunity to experience them.
Envrionmental Archaeology, Fire Ecology, GIS, Agent-based modeling, Geoarchaeology
Amin is a PhD student in the quantitative and systems biology graduate program at UC Merced. He has been passionate about entrepreneurship since his undergraduate years in his hometown of Isfahan and then later in Bologna, Italy, where he completed his masters. Once a recipient of the Innovators Under 35 Award in Italy, he believes there is massive opportunity for society to train and motivate younger minds to acquire an entrepreneurial mindset, along with entrepreneurship skills.
Entrepreneurship, management, mathematical modeling, agent based modeling.
My research focuses on building a systemic understanding of coupled human-natural systems. In particular, I am interested in understanding how patterns of land-use and land-cover change emerge from human alterations of natural processes and the resulting feedbacks. Study systems of interest include those undergoing agricultural to urban conversion, typically known as urban sprawl, and those in which protective measures, such as wildfire suppression or flood/storm impact controls, can lead to long-term instability.
Dynamic agent- and process-based simulation models are my primary tools for studying human and natural systems, respectively. My past work includes the creation of dynamic, process-based simulation models of the wildland fires along the urban-wildland interface (UWI), and artificial dune construction to protect coastal development along a barrier island coastline. My current research involves the testing, refinement, extension of an economic agent-based model of coupled housing and land markets (CHALMS), and a new project developing a generalized agent-based model of land-use change to explore local human-environmental interactions globally.
I have a strong background in building and incorporating agent-based simulations for learning. Throughout my graduate career, I have worked at the Center for Connected Learning and Computer Based Modeling (CCL), developing modeling and simulation tools for learning. In particular, we develop NetLogo, the gold standard agent-based modeling environment for learners around the world. In my dissertation work, I marry biology and computer science to teach the emergent principles of ant colonies foraging for food and expanding. The work builds on more than a decade of experience in ABM. I now work at the Center for the Science and the Schools as an Assistant Professor. We delivered a curriculum to teach about COVID-19, where I incorporated ABMs into the curriculum.
You can keep up with my work at my webpage: https://kitcmartin.com
Studying the negative externalities of networks, and the ways in which those negatives feedback and support the continuities.
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