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Sedar is a PhD student at the University of Leeds, department of Geography. He graduated in Computer Science at King’s College London 2018. From a very early stage of his degree, he focused on artificial intelligence planning implementations on drones in a search and rescue domain, and this was his first formal attempt to study artificial intelligence. He participated in summer school at Boğaziçi University in Istanbul working on programming techniques to reduce execution time. During his final year, he concentrated on how argumentation theory with natural language processing can be used to optimise political influence. In the midst of completing his degree, he applied to Professor Alison Heppenstall’s research proposal focusing on data analytics and society, a joint endeavour with the Alan Turing Institute and the Economic and Social Research Council. From 2018 - 2023 he will be working on his PhD at the Alan Turing Institute and Leeds Institute for Data Analytics.
Sedar will be focusing on data analytics and smart cities, developing a programming library to try simulate how policies can impact a small world of autonomous intelligent agents to try deduce positive or negative impact in the long run. If the impact is positive and this is conveyed collectively taking into consideration the agent’s health, happiness and other social characteristics then the policy can be considered. Furthermore, he will work on agent based modelling to solve and provide faster solutions to economic and social elements of society, establishing applied and theoretical answers. Some other interests are:
Moscow City University, Professor: Institute of Digital Education - http://digida.mgpu.ru
National Research University Higher School of Economics, Professor: Institute of Education / Department of Educational Programmes. Leading Expert: Institute of Education / Laboratory for Digital Transformation of Education - 2019 – present
2016 – present Leading Researcher at Moscow City University, Educational policies & educational practices
2018 – 2020 World Bank, Consultant. Children Learning to Code: Essential for 21st Century Human Capital
2011 - 2019 - Co-founder, chief community officer at WikiVote!
Educational network - Letopisi.org 2006 – present, Co-founder, chief community officer
Scientific project “Mobile and ubi-learning”, 2009 - 2011
ABM, wiki, NetLogo, StarLogo Nova, R, Collaboration
Moira Zellner’s academic background lies at the intersection of Urban and Regional Planning, Environmental Science, and Complexity. She has served as Principal Investigator and Co-Investigator in interdisciplinary projects examining how specific policy, technological and behavioral factors influence the emergence and impacts of a range of complex socio-ecological systems problems, where interaction effects make responsibilities, burdens, and future pathways unclear. Her research also examines how participatory complex systems modeling with stakeholders and decision-makers can support collaborative policy exploration, social learning, and system-wide transformation. Moira has taught a variety of courses and workshops on complexity-based modeling of socio-ecological systems, for training of researchers, practitioners, and decision-makers in the US and abroad. She has served the academic community spanning across the social and natural sciences, as reviewer of journals and grants and as a member of various scientific organizations. She is dedicated to serving the public through her engaged research and activism.
Applications of agent-based modeling to urban and environmental planning
Participatory modeling
I am a Research Associate with an interdisciplinary background spanning economics, social sciences, and international relations. After several years of professional experience outside academia, I now focus on applying agent-based modeling to management control challenges. My research explores how organizations can mitigate dysfunctional behaviors such as lying, fraud, and other forms of opportunism, aiming to design control systems that balance the pursuit of organizational goals while maintaining individual and organizational integrity.
Paul Hart BSc (Liverpool), BA (Open University), PhD (Liverpool), MAE, FLS, FMBA. From 1973-1976 I worked on the Continuous Plankton Recorder (CPR) survey at the Oceanographic Laboratory, Edinburgh. From 1973 – 1976 I was employed by Nordreco AB (a Nestlé R & D company) in Sweden as a fishery biologist where he advised the Findus group on fish raw material supplies and assessed the future potential of aquaculture. In 1976 I moved to the University of Leicester as a lecturer in aquatic biology. My research focused on the foraging behaviour of fish with a side interest in marine commercial fisheries. I retired as Professor and Head of the Department of Biology and am now an Emeritus Professor. I was a Trustee of the Sir Alister Hardy Foundation for Ocean Science, which ran the Continuous Plankton Recorder Survey until it was merged with the Marine Biological Association: I then became a Trustee of the MBA. From 2010 – 2016 I was a member of the Science Advisory Board of Marine Scotland. I am co-author of Fisheries Ecology (1982) and co-editor of the two-volume Handbook of Fish Biology and Fisheries (2002). I was a co-editor of the journal Fish and Fisheries (Wiley) between 2000 and 2021.
IBMs of fisheries exploring management options and consequences of social behaviour.
I have been researching in synchronization between agent-based-models (ABM) and multi robot systems used in logistic and manufacturing. I use Netlogo as ABM.
I develop and agile methodology to use the same ABM as supervisory control and data aquisition (SCADA). The framework works fine and I test it in two SCADAs, which you can see in my youtube channel (http://www.youtube.com/channel/UCJIb_UL-ak98F5OZxOHL0FQ).
Interested in numerical models and new conceptual ideas, applications from industry to medicine.
I focus on numerical modeling of mechanics of solid materials and cell mechanics. The models that I developed so far address granular matters, bio-fluids, cellular tissues, and individual cells.
I further develop Agent-based Models, which are methods to predict collective behavior from individual dynamics controlled by rules or differential equations. Examples: tumor growth, swarms, crowd movement.
The methods I used are Particle-based methods which offer great flexibility within physical modeling, and can operate in a large range of scales, from atomistic scales (e.g. Molecular Dynamics) to continuum approaches (e.g. Smoothed Particle Hydrodynamics).
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Displaying 10 of 95 results for "Viet Cao" clear search