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Dr. Chairi Kiourt is a research associate with the ATHENA - Research and Innovation Centre in Information, Communication and Knowledge Technologies - Xanthi’s Division, multimedia department since 2014. Also, as of December 2017, heis PostDoctoral researcher with the Hellenic Open University, School of Science and Technology, and as of 2018, visiting Lecturer at the Department of Informatics Engineering, Eastern Macedonia and Thrace Institute of Technology, Greece.
In 2003, he received his BSc degree in Electrical Engineering from the Electrical Engineering Department of the Eastern Macedonia and Thrace Institute of Technology, Greece. He also received an M.Sc. in System Engineering and Management in the specialty area: A. Information and Communication Systems Management from the Democritus University of Thrace, Greece. In 2017, received his PhD in Artificial Intelligence and Software Engineering from the Hellenic Open University. He has participated in several national and European research programs and co- authored to the writing of several scientific publications in international peer-reviewed journals and conferences with judges in the fields of collective artificial intelligence, multi-agent systems, reinforcement learning agents, virtual worlds, virtual museums and gamification.
Game playing multi-agent systems, reinforcement learning, colelctive artificial intelligence, distributed computing systems, virtual worlds, gamification
I am a University Academic Fellow (UAF) in the School of Geography at the University of Leeds. My research areas are agent-based modelling, decision making in complex systems, AI and multi-agent systems, urban analytics and housing markets. I obtained PhD in Economics from Iowa State University under supervisor Prof. Leigh Tesfatsion in 2014. I worked as a researcher at the James Hutton Institute in Aberdeen, Scotland between 2014 and 2019. I joined the University of Leeds as a UAF of Urban Analytics in 2019. I am originally from Shanghai, China.
My main research areas are agent-based modelling, urban analytics and complex decision making enabled by AI. I am interested in the bottom-up transition of complex urban systems under major socio-economic and environmental shocks, such as climate change and the fourth industrial revolution. I want to understand how cities as self-organised complex systems respond to external shocks and evolve under a constantly changing environment. In the past, I have looked at various aspects of urban systems, including the housing market, the labour market, transport and energy system. I am also interested in decision making in complex systems. For example, I have studied the decision to become a vegetarian/vegan under social influence. I have also looked at global food trade in a complex trade network and the resulting food and nutrition security. Recently, I am interested in applying AI algorithms especially reinforcement learning in multi-agent systems, including applications of AI in urban adaptation to climate change, housing market dynamics and criminal behaviour in an urban system.
Machine Learning, Artifical Inteligence, Multi Agent Simulations
Furkan Gürsoy received the BS in Management Information Systems from Boğaziçi University, Turkey, and the MS in Data Science from İstanbul Şehir University, Turkey. He is currently a PhD Candidate at Boğaziçi University. He previously worked as an IS/IT Consultant and a Machine Learning Engineer with the industry for several years. He held a Visiting Researcher Position with IMT Atlantique, France, in 2020. His research interests include complex networks, machine learning, simulation, and broad data science.
network science, machine learning, simulation, data science.
Farzaneh Davari is a social science researcher who has worked in many diverse fields, including agriculture, conflict, health, and human rights, just to name a few. Currently, she is a Ph.D. candidate in Computational Social Science, focusing on social-ecological complex systems and applying computational science and Agent-Based Modeling to understand resilience procedure through self-organizing and learning. Meanwhile, she is a designer and instructor of the online graduate level course of Decision-making in Complex Environments in Virginia Tech.
Social-ecological complex system, resilience-building, conflictual environment
My initial training was in cadastre and geodesy (B.Eng from the Distrital University, UD, Colombia). After earning my Master’s degree in Geography (UPTC, Colombia) in 2003, I worked for the “José Benito Vives de Andreis” marine and coastal research institute (INVEMAR) and for the International Center for Tropical Agriculture (CIAT). Three years later, in 2006, I left Colombia to come to Canada, where I began a PhD in Geography with a specialization in modelling complex systems at Simon Fraser University (SFU), under the direction of Dr. Suzana Dragicevic (SAMLab). In my dissertation I examined the topic of spatial and temporal modelling of insect epidemics and their complex behaviours. After obtaining my PhD in 2011, I began postdoctoral studies at the University of British Columbia (2011) and the University of Victoria (2011-2013), where I worked on issues concerning the spatial and temporal relationships between changes in indirect indicators of biodiversity and climate change.
I am an Associate Professor in the Department of Geography at the University of Montreal. My research interests center around the incorporation of artificial intelligence and machine learning techniques into the development Agent-Based Models to solve complex socio-ecological problems in different kind of systems, such as urban, forest and wetland ecosystems.
The core of my research projects aim to learn more about spatial and temporal interactions and relationships driving changes in our world, by focusing on the multidisciplinary nature of geographical information science (GIScience) to investigate the relationships between ecological processes and resulting spatial patterns. I integrate spatial analysis and modeling approaches from geographic information science (GIScience) together with computational intelligence methods and complex systems approaches to provide insights into complex problems such as climate change, landscape ecology and forestry by explicitly representing phenomena in their geographic context.
Specialties: Agent-based modeling, GIScience, Complex socio-environmental systems, Forestry, Ecology
The big picture question driving my research is how do complex systems of interactions among individuals / agents result in emergent properties and how do those emergent properties feedback to affect individual / agent decisions. I have explored this big picture question in a number of different contexts including the evolution of cooperation, suburban sprawl, traffic patterns, financial systems, land-use and land-change in urban systems, and most recently social media. For all of these explorations, I employ the tools of complex systems, most importantly agent-based modeling.
My current research focus is on understanding the dynamics of social media, examining how concepts like information, authority, influence and trust diffuse in these new media formats. This allows us to ask questions such as who do users trust to provide them with the information that they want? Which entities have the greatest influence on social media users? How do fads and fashions arise in social media? What happens when time is critical to the diffusion process such as an in a natural disaster? I have employed agent-based modeling, machine learning, geographic information systems, and network analysis to understand and start to answer these questions.
Mathematical modeling
agent-based modeling
coupling of agent-based models and mathematical models
machine learning algorithms
deep learning algorithms
Statistical inference
infectious diseases modeling
B.S. in Fish and Wildlife from Michigan State University in 1996. M.S. in Wildlife Ecology from the University of Maine - Orono in 2001. Employed by the Michigan Department of Natural Resources since 2003, first as a field biologist (2003-2008), then statewide endangered species coordinator (2008-2012), and currently as the statewide (climate) adaptation program lead (2012-present). Also currently a graduate student in the Boone and Crockett Quantitative Wildlife Center at Michigan State University (2015-present). Father, gardener, hiker, and amateur myxomycologist.
Human-wildlife social-ecological systems, resilience and learning in complex adaptive systems, climate change, disturbance ecology, and historical ecology
Leonardo Grando is a Ph.D. Student at the University of Campinas (UNICAMP) in Brazil. I am interested in complex systems, agent-based simulation, artificial intelligence, the Internet of Things, programming, and machine learning tools. I have expertise in Netlogo, Python, R, Latex, SQL, and Linux tools.
My Ph.D. work project is an IoT devices (UAVs) swarm agent-based modeling simulation (ABMS) aiming the perpetual flight. The workflow is Netlogo to ABMS simulate, Python and R to data analysis, and I use Latex for my thesis writing.
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