Chico Camargo is a Postdoctoral Researcher in Data Science. He develops and applies computational tools to study collective human behaviour, focusing on public opinion dynamics and human mobility.
Email: chico.camargo@oii.ox.ac.uk
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Dr Chico Camargo is a Postdoctoral Researcher in Data Science. He uses tools from complex systems and data science to develop new computational approaches to questions in the social sciences, focusing on public opinion dynamics, information dynamics and human mobility. He is also a member of the #SocialHumanities network and of the PastNet network, at The Oxford Research Centre in the Humanities (TORCH).
Chico graduated with a BSc from the University of São Paulo, as part of the Molecular Sciences Programme, and later worked in mathematical modelling in biology at the Wolfson Centre for Mathematical Biology, and at the Department of Zoology, University of Oxford. He then moved to a PhD (DPhil) in systems biology, also at Oxford, as a Clarendon Scholar in Brasenose College. In his PhD research, he used tools from complex systems and machine learning to investigate the physical principles that rule biological evolution.
Apart from doing science himself, Chico is also passionate about communicating it to wider audiences. He has spoken at science communication events such as FameLab, as well as Oxford’s Science Cabaret, and is also part of the award-winning YouTube educational channel BláBláLogia, which hosts videos in Portuguese on topics ranging from space travel to ecology to film making. In his show, Top Models, Chico speaks about his favourite scientific tool: mathematical models.
Position held at OII:
- Postdoctoral Researcher in Data Science, January 2018 –
- Research Assistant in Complex Networks, May 2017 – 2018
Research Interests:
computational social science, social data science, digital humanities, cultural evolution, collective behaviour, applications of machine learning, natural language processing (NLP), public opinion dynamics, complex systems, data visualisation
Latest blog posts
Current projects
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TRANSNET: Forecasting and understanding transport network resilience and anomalies
Participants: Dr Scott A. Hale, Dr Jonathan Bright, Dr Graham McNeill, Chico Camargo
This project seeks to utilise newly available data to help urban policy makers improve transport infrastructure to cope with growing and increasingly mobile populations.
Past projects
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Transnet: Understanding traffic with open data and visualization
Recorded: 26 July 2018
Duration: 00:42:30
This presentation, hosted by the Alan Turing Institute focuses on using crowd-sourced data, such as OpenStreetMap and Waze, to improve traffic models and better understand the factors contributing to traffic jams and other traffic issues.