Factmata is built upon cutting-edge academic research in natural language processing and information retrieval. We are launching a state-of-the-art fact-checking system using machine intelligence, for statistical claims made in digital media content, such as news articles and political speech transcripts.
Our first goal is to make fact-checking more automated, more fun and easier. We want to build a product that engages people in the process of correcting news articles, identifying fallible claims, and supporting more accurate information on the web.
We hope to apply state of the art artificial intelligence to broader misinformation problems that exist on the web. This includes automated systems for detecting fake news, tracking rumours and hoaxes, tracking promises and many more. We believe that misinformation leads to mistrust, and this leads to broader social and political problems.
Our mission is to protect people from misleading information they are exposed to on a daily basis, and empower them to not take anything for granted.
Chief NLP Architect
Thiago holds a PhD in Computational Linguistics from UCL, and is an Natural Language Processing (NLP) engineer with 4+ years of academic experience and 5+ years of industry experience. His experience includes the development of a grammar for sentiment analysis at IBM text-analytics (Germany), a semantic recommendation engine/personalisation system at Idio (London), and the implementation of a Named Entity Recognition and Entity Linking pipeline for Signal’s news tracking service (London,UK). He is a consultant for one of the most reputed pieces of ML/NLP software, gensim, develops and maintains NLP services for CompyAdvantage’s apis, and contributes to the well-known open source Entity Linking system known as DBpedia Spotlight.
CEO and Research Scientist
Dhruv holds a Distinction in Computer Science and Machine Learning from University College London, and a 1st Class BSc in Economics from the LSE. He was a product manager and co-founder of two London based machine intelligence startups, and Entrepreneur First alum. He wrote his thesis in cost-sensitive classification and distant supervision for statistical claim detection.
Rishabh has been the CTO at Neuron, a New Delhi based machine learning startup, and involved with research and development of Scalable Deep Learning Models for Natural Language Processing (NLP). He is an active open source contributor and Google Summer of Code Intern. He is interested in working with Generative Models and carrying out research work in the field of Natural Language Understanding (NLU), and holds a Bachelor in Technology (B.Tech) from SMVDU, Jammu.
Sebastian is a Reader at University College London and leading the Machine Reading Lab. He is an Allen Distinguished Investigator, Marie Curie fellow and received a Google Focused Research award. Sebastian is generally interested in the intersection of Natural Language Processing and Machine Learning, and particularly interested in teaching machines to read and to reason with what was read. He has published various papers on this topic, covering questions related to scalable inference, probabilistic programming and representation learning.
Chief Research Scientist
Andreas is a lecturer at the University of Sheffield, working on the intersection of Natural Language Processing and Machine Learning. Current projects include natural language generation, automated fact-checking and imitation learning. He has also published research on semantic parsing, language modelling, information extraction, active learning, clustering and biomedical text mining.