Displaying 9 of 29 results for "Hosang Shin" clear search
Inyoung Hwang is an Associate Research Fellow at Korea Institute of Science & Technology Evaluation and Planning (KISTEP), South Korea. He was a visiting scholar in the School of Public Affairs at Arizona State University. He received a B.Sc. in Vocational Education and Workforce Development, an M.P.P. in Public Policy, and a Ph.D. in Public Policy from Seoul National University.
Science & Technology Policy, Collaborative Innovation, Technological Diffusion and Convergence, Agent-Based Modelling, and Social Simulation.
I am a full professor at the College of Economics and Management, Huazhong Agricultural University, and the Executive Dean of the Digital Agriculture Research Institute.
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.
Dr. Saeed Moradi received his Ph.D. in Civil Engineering from Texas Tech University in Lubbock, Texas. Saeed has 11+ years of experience in research, policymaking, housing sector, construction management, and structural engineering. His career developed his enthusiasm for the enhancement of post-disaster recovery plans. Through his research on disaster recovery, community resilience, and human-centered complex systems, Saeed aims to bridge the gap between social sciences and civil/infrastructure engineering.
Community and Infrastructure Resilience
Disaster Recovery
Complex Systems Modeling
Agent-Based Modeling
System Dynamics
Machine Learning
Pattern Recognition
Data Mining
Spatial Analysis and Modeling
Construction Management
Building Information 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
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Associate Professor
School of Management Science and Engineering, Shandong Technology and Business University (Yantai 264005, P. R. China)
Ph. D. Degree, 09/2009 – 07/2015
School of Economics and Management, Beihang University (P. R. China)
M. A. Degree, 09/2003 – 02/2006
The Institute of Systems Engineering, Dalian University of Technology (P. R. China)
B. A. Degree, 09/1999 – 07/2003
Department of Information and Control Engineering, Zhengzhou University of Light Industry (P. R. China)
Visiting Scholar at GECS – Research Group of Experimental and Computational Sociology (March, 2017 – February, 2018)
Università degli Studi di Brescia (Italy)
Co-supervisor: Professor Flaminio Squazzoni
Summer school in ‘Agent-based modeling for social scientists’ (September 4-8, 2017)
University of Brescia, Italy
Instructors: Flaminio Squazzoni, Simone Gabbriellini, Nicolas Payette, Federico Bianchi
The Santa Fe Institute’s Massive Open Online Course: Introduction to Agent-Based Modeling (Jun 5 – September 8, 2017)
The Santa Fe Institute, Complexity Explore Web: abm.complexityexploer.org
Instructors: Bill Rand
Summer school in ‘Complex systems and management’ (July 2-12, 2012)
National Defense University, P. R. China
Instructors: Xinjun Mao, Yongfang Liu, Dinghua Shi, Qiyue Cheng
Routine dynamics, Agent-based modeling, Computational social/organization science, Industrial systems engineering, etc.
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.
Volker Grimm currently works at the Department of Ecological Modelling, Helmholtz-Zentrum für Umweltforschung. Volker does research in ecology and biodiversity research.
How to model it: Ecological models, in particular simulation models, often seem to be formulated ad hoc and only poorly analysed. I am therefore interested in strategies and methods for making ecological modelling more coherent and efficient. The ultimate aim is to develop preditive models that provide mechanstic understanding of ecological systems and that are transparent and structurally realistic enough to support environmental decision making.
Pattern-oriented modelling: This is a general strategy of using multiple patterns observed in real systems as multiple criteria for chosing model structure, selecting among alternative submodels, and inversely determining entire sets of unknown model parameters.
Individual-based and agent-based modelling: For many, if not most, ecological questions individual-level aspects can be decisive for explaining system-level behavior. IBM/ABMs allow to represent individual heterogeneity, local interactions, and/or adaptive behaviour
Ecological theory and concepts: I am particularly interested in exploring stability properties like resilience and persistence.
Modelling for ecological applications: Pattern-oriented modelling allows to develop structurally realistic models, which can be used to support decision making and the management of biodiversity and natural resources. Currently, I am involved in the EU project CREAM, where a suite of population models is developed for pesticide risk assessment.
Standards for model communication and formulation: In 2006, we published a general protocol for describing individual- and agent-based models, called the ODD protocol (Overview, Design concepts, details). ODD turned out to be more useful (and needed) than we expected.
Displaying 9 of 29 results for "Hosang Shin" clear search