Welcome! Nigel is a Principal Research Associate in the Department of Theoretical and Applied Linguistics (DTAL) at the University of Cambridge where he co-founded the Language Technology Laboratory. He is also a Visiting Scientist at the European Bioinformatics Institute (EMBL-EBI), a member of the EPSRC Peer Review College (2015- present), an elected member of the faculty board in Modern and Medieval Languages (2016-2018) and a study steering committee member on the NIHR DEPEND project (2015-2018). Nigel has extensive research expertise in Computational Linguistics. He is currently funded by a 1.2 million 5-year EPSRC fellowship to investigate the Semantic Interpretation of Personal Health messages on the Web (SIPHS) project. This is an international collaborative effort to leverage social media data for digital disease applications such as detecting infectious disease outbreaks and adverse drug reaction.
Nigel's research interests bring together computational techniques such as machine learning, syntactic parsing and concept understanding with the aim of providing a machine-understandable semantic representation of text. This is used to support real-world tasks, e.g. biomedical text mining, question answering and knowledge discovery. He has published over 100 peer-reviewed papers with >3600 citations and a h-index >29 by Google Scholar. He is a senior member of the Association for Computing Machinery (1996 - present) and a member of the Association for Computational Linguistics (1996 - present).
Prior to joining the University of Cambridge Nigel was a FP7 Marie Curie fellow on the PhenoMiner project at EMBL-EBI (2012-2014) and Associate Professor at the National Institute of Informatics in Tokyo where he led the Natural Language Processing laboratory. From 2007 - 2012 he served as a technology advisor on the international Global Health Security Action Group technical working group on Risk Management and Communication. He obtained his PhD in computational linguistics at UMIST in 1996 (now the University of Manchester) for his research into the application of neural networks for machine translation.