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Christopher Parrett Member since: Sunday, October 20, 2019 Full Member

I am a lowly civil servant moonlighting as a PhD student interested in urban informatics, Smart Cities, artificial intelligence/machine learning, all-things geospatial and temporal, advanced technologies, agent-based modeling, and social complexity… and enthusiastically trying to find a combination thereof to form a disseration. Oh… and I would like to win the lottery.

  • Applied data science (machine/deep learning applications) and computational modeling (agent-based
    modeling) in U.S. Government
  • Geographic Information Systems and analysis of dense urban environments and complex terrain
  • Complexity theory and computational organizational design of distributed enterprise teams.
  • Human Capital Management and Talent Management policy development

Sedar Olmez Member since: Wednesday, November 06, 2019 Full Member

MSci in Computer Science, MSc in Data Analytics and Society

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:

  • Multi-agent systems
  • Intelligent agents
  • Natural language processing
  • Artificial intelligence planning
  • Machine learning
  • Neural networks
  • Genetic programming
  • Geocomputation
  • Argumentation theory
  • Smart cities

Sam Battherford Member since: Thursday, July 15, 2021

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