Imperial College London

DrJulioAmador Diaz Lopez

Business School

Imperial College Research Fellow







Business School BuildingSouth Kensington Campus





Julio holds a PhD in economics from the University of Essex. His area of expertise is applied machine learning (ML). Julio has held different research positions, both in the UK and abroad, and is now a research associate at Imperial Business Analytics, a laboratory held together by Imperial College’s Data Science Institute and Business School. His research includes big-data studies of online political participation and applying ML to categorize public opinion and automatically identifying fake news. Julio is currently dedicated to the study of misinformation.



Oehmichen A, Hua K, Lopez JAD, et 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, ISSN:2169-3536, Pages:126305-126314

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, et al., 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, et al., 2017, Predicting the Brexit Vote by Tracking and Classifying Public Opinion Using Twitter Data, Statistics, Politics and Policy, Vol:8, ISSN:2151-7509

L�pez JCAD, Pi�a-Garc�a CA, 2017, Political participation in Mexico through twitter, Studies in Computational Intelligence, Vol:693, ISSN:1860-949X, Pages:607-618

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