Regular biography
Prof Andreas Vlachos is a Fellow at the University of Cambridge, affiliated with the Department of Computer Science and Technology. His research interests include Natural Language Processing and Machine Learning, with current projects focusing on dialogue modelling, automated fact checking, and imitation learning. He has also contributed to semantic parsing, natural language generation, summarization, language modelling, information extraction, active learning, clustering, and biomedical text mining. His work is supported by various funding bodies and industry partners. Prior to his current role, he was a lecturer at the University of Sheffield and held postdoctoral positions at UCL, the University of Cambridge, and the University of Wisconsin-Madison. He completed his PhD at the University of Cambridge.
Scholar-generated biography
Andreas Vlachos is a professor at the University of Cambridge, specializing in natural language processing and machine learning. His research focuses on fact extraction, verification, and automated fact-checking, with an emphasis on developing datasets and methodologies for detecting misinformation. He has contributed to large-scale projects such as FEVER and FEVER2.0, which aim to improve the accuracy of fact verification systems. His work also includes stance detection, authorship attribution, and semantic parsing. Vlachos has explored the use of neural networks and ensemble methods for tasks like fake news detection and nested named entity recognition.