Talk, University of Florida, Gainesville, FL
How have Russian information campaigns influenced and affected public perceptions of the Russo-Ukrainian War? In this talk, we study the coordinated information campaign to understand the most prominent disinformation narratives touted by the Russian government to English-speaking audiences.
Talk, University of Central Florida, Orlando, FL
How have Russian information campaigns influenced and affected public perceptions of the Russo-Ukrainian War? In this talk, we study the coordinated information campaign to understand the most prominent disinformation narratives touted by the Russian government to English-speaking audiences.
Talk, Stanford Security Lunch, Stanford, CA
In this work, we study the most prominent disinformation narratives being touted by the Russian government to English-speaking audiences. To do this we perform topic analysis using the large-language model MPNet on articles published by nine different Russian disinformation websites and the new Russian “fact-checking” website waronfakes.com. We then map Reddit comments to the topics being promoted by these disinformation websites.
Talk, Stanford Security Workshop, Stanford, CA
In this work, we study the relationships between five prominent conspiracy theories (QAnon, COVID, UFO/Aliens, 9/11, and Flat-Earth) and the role that misinformation and political polarization play in spreading these conspiracies.
Talk, Stanford Security Lunch, Stanford, CA
In this talk, we explore using web crawls seeded from two of the largest QAnon hotbeds on the Internet, Voat and 8kun, to build a hyperlink graph in order to study the QAnon conspiracy theory.
Talk, 2020 3rd RSC-BMCS / RSC-CICAG Artificial Intelligence in Chemistry, London, UK
We propose a novel machine learning architecture and technique for de novo drug discovery of anti-cancer drugs by using discrete representations of drugs’ chemical compositions and the transcriptomics of targets.
Talk, 2019 Oxford Computer Science Conference, Oxford, England
This work focuses on utilizing Transformer and CNN machine translation models to learn contextualized word representations for use in sentiment classification.
Talk, 2019 Oxford Computer Science Conference, Oxford, England
This talk concerns counteracting information leakage in Tor relay selection algorithms.