| Honorific Suffix: | FRSE |
| Fields: | |
| Alma Mater: | |
| Workplaces: | University of Edinburgh University of Sheffield |
| Thesis Title: | Acquisition and modeling of lexical knowledge: a corpus-based investigation of systematic polysemy |
| Thesis Url: | https://www.era.lib.ed.ac.uk/handle/1842/22394 |
| Thesis Year: | 2000 |
| Doctoral Advisors: |
|
Mirella Lapata FRSE is a computer scientist and Professor in the School of Informatics at the University of Edinburgh.[1] Working on the general problem of extracting semantic information from large bodies of text, Lapata develops computer algorithms and models in the field of natural language processing (NLP).
Lapata obtained an Master of Arts (MA) degree from Carnegie Mellon University and subsequently earned a doctorate from the University of Edinburgh.[2] Lapata's doctoral research investigated the acquisition of information from polysemous linguistic units using probabilistic methods supervised by Alex Lascarides, Chris Brew and Steve Finch.[3]
After her doctorate, Lapata assumed academic positions at Saarland University and at the Department of Computer Science at the University of Sheffield.[4] At the University of Edinburgh she became a reader in the School of Informatics where she is a full Professor and holds a personal chair in natural language processing.[5] Lapata is a member of the Human Communication Research Center and Institute for Language, Cognition and Computation, both in Edinburgh.[6]
Between 2015 and 2017, Lapata served as a member of the Royal Society Machine Learning Working Group.[7] Recently Lapata was granted a European Research Council (ERC) Consolidator Grant worth €1.9M to fund five years of her project, TransModal: Translating from Multiple Modalities into Text.[8]