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Sudhira’s research has been primarily on urban land-use and land cover change studies exploring their consequences on environmental sustainability and understanding their inter-relationship with transportation. His broader research addresses the evolution and growth of towns and cities invoking complexity sciences, understanding planning practices and studying the effect of varied governance structures.
S.R. Aurora, also known as Mai P. Trinh, is an Assistant Professor of Management at The University of Texas Rio Grande Valley. Her interdisciplinary work intersects leadership, complex systems science, education, technology, and inclusion. Her research harnesses technology to cultivate future leaders and helps people thrive in our volatile, uncertain, complex, and ambiguous (VUCA) high-tech world, aligning with four United Nations’ sustainable development goals: Quality education (#4), Gender equality (#5), Decent work and economic growth (#8), and Reduced inequalities (#10). She has published in top-tiered peer-reviewed journals such as The Leadership Quarterly and The Academy of Management Learning and Education and received multiple national and international awards for her research, teaching, and mentoring. Dr. Aurora earned her doctoral degree in Organizational Behavior from the Weatherhead School of Management at Case Western Reserve University in 2016.
Leader development, leading complex systems, agent-based modeling, experiential learning, innovations in online education
I studied Molecular Biology and Genetics at Istanbul Technical University. During my undergraduate studies I became interested in the field of Ecology and Evolution and did internships on animal behaviour in Switzerland and Ireland. I then went on to pursue a 2-year research Master’s in Evolutionary Biology (MEME) funded by the European Union. I worked on projects using computer simulations to investigate evolution of social complexity and human cooperation. I also did behavioural economics experiments on how children learn social norms by copying others. After my Master’s, I pursued my dream of doing fieldwork and investigating human societies. I did my PhD at UCL, researching cultural evolution and behavioural adaptations in Pygmy hunter-gatherers in the Congo. During my PhD, I was part of an inter-disciplinary Hunter-Gatherer Resilience team funded by the Leverhulme Trust. I obtained a postdoctoral research fellowship from British Academy after my PhD. I am currently working as a British Academy research fellow and lecturer in Evolutionary Anthropology and Evolutionary Medicine at UCL.
My research is focused on autonomous agents and multiagent systems. Specifically: Trust and reputation models, cognitive architectures, cognitive models and social simulation.
PhD student, ecology and evolutionary biology
Ecological theory and modeling
Gerd Wagner is Professor of Internet Technology at Brandenburg University of Technology, Cottbus, Germany. After studying Mathematics, Philosophy and Informatics in Heidelberg, San Francisco and Berlin, he (1) investigated the semantics of negation in knowledge representation formalisms, (2) developed concepts and techniques for agent-oriented modeling and simulation, (3) participated in the development of a foundational ontology for conceptual modeling, the Unified Foundational Ontology (UFO), and (4) created a new Discrete Event Simulation paradigm, Object Event Modeling and Simulation (OEM&S), and a new process modeling language, the Discrete Event Process Modeling Notation (DPMN). Much of his recent work on OEM&S and DPMN is available from sim4edu.com.
Modeling and simulation of agents and other discrete systems.
energy and environmental sciences
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.
My research interests include policy informatics and decision making, modeling in policy analysis and management decisions, public health management and policy, and the role of public value in policy development. I am particularly interested in less mainstream approaches to modeling that account for learning, feedback, and other systems dynamics. I include Bayesian inference, agent-based models, and behavioral assumptions in both my research and teaching.
In my dissertation research, I conceptualize state Medicaid programs as complex adaptive systems characterized by diverse actors, behaviors, relationships, and objectives. These systems reproduce themselves through both strategic and emergent mechanisms of program management. I focus on the mechanism by which citizens are sorted into or out of the system: program enrollment. Using Bayesian regression and agent-based models, I explore the role of administrative practices (such as presumptive eligibility and longer continuous eligibility periods) in increasing enrollment of eligible citizens into Medicaid programs.
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