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Julio Amador

Assistant Professor, Game Theroy and Machine Learning at The London School of Economics and Political Science

Research Associate at Imperial College London

Schools

  • Imperial College London
  • The London School of Economics and Political Science

Links

Biography

The London School of Economics and Political Science

Julio holds a PhD in economics from the University of Essex. His area of expertise is applied game theroy and machine learning. Julio has held different research positions, both in the UK and abroad, and was previously a research associate at Imperial Business Analytics, a laboratory held together by Imperial College’s Data Science Institute and Business School.

Julio's research includes big-data studies of online political participation and applying machine learning to categorize public opinion and automatically identifying fake news. Julio is currently dedicated to the study of misinformation.

Key Expertise

  • Machine Learning, Misinformation, Game Theory

Languages

  • English

Education

  • PhD University of Essex (2009 — 2012)
  • MSc University of Essex (2008 — 2009)
  • BA Tecnológico de Monterrey (2004 — 2008)

Publications

  • Fernando S, AmadorDíazLópez J, Şerban O, Gómez-Romero J, Molina-Solana M, Guo Yet al., 2020, Towards a large-scale twitter observatory for political events, Future Generation Computer Systems, Vol: 110, Pages: 976-983, ISSN: 0167-739X

  • Oehmichen A, Hua K, Diaz Lopez JA, Molina-Solana M, Gomez-Romero J, Guo Y-Ket al., 2019, Not All Lies Are Equal. A Study Into the Engineering of Political Misinformation in the 2016 US Presidential Election, IEEE ACCESS, Vol: 7, Pages: 126305-126314, ISSN: 2169-3536

  • Molina-Solana M, Kennedy M, Amador Diaz Lopez J, 2018, foo.castr: visualising the future AI workforce, Big Data Analytics, Vol: 3, ISSN: 2058-6345

  • Piña-Garcia CA, Siqueiros-Garcia JM, Robles-Belmont E, Carreon G, Gershenson C, Amador Diaz Lopez JCet al., 2017, From Neuroscience to Computer Science: A Topical Approach on Twitter, Journal of Computational Social Science, ISSN: 2432-2717

  • Amador Diaz Lopez JC, Collignon-Delmar S, Benoit K, Matsuo Aet al., 2017, Predicting the Brexit Vote by Tracking and Classifying Public Opinion Using Twitter Data, Statistics, Politics and Policy, Vol: 8, ISSN: 2151-7509

  • Lpez JCAD, Pia-Garca CA, 2017, Political participation in Mexico through twitter, Studies in Computational Intelligence, Vol: 693, Pages: 607-618, ISSN: 1860-949X

  • Amador Diaz Lopez JC, Piña García C, 2017, Political Participation in Mexico Offline and Through Twitter, Online Communities As Agents of Change and Social Movements, Editors: Gordon, Publisher: Information Science Reference, ISBN: 9781522524953

  • Amador J, Oehmichen A, Molina-Solana M, Characterizing Political Fake News in Twitter by its Meta-Data

Imperial College London

Summary

Julio holds a BSc in economics from Tecnologico de Monterrey and an MSc and PhD in economics from the University of Essex, UK. His area of expertise is social and economic networks. At Essex, he worked under the supervision of Prof. Andrea Galeotti, where he dedicated himself to the study of games in networks. Julio has participated as a research assistant to Prof. Galeotti at the EssexLab, where they conducted experiments on trading in social networks. Furthermore, he collaborated as a research fellow at the Department of Government at the University of Essex, where he carried out quantitative analysis of public opinion. Julio has held positions of assistant professor at CIDE and part-time lecturer at EGADE Business School. He is now research associate at Imperial Business School where he is currently dedicated to study advertising in social networks, micro-finance and data-mining algorithms.

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