UKRI Centre for Doctoral Training in Natural Language Processing
Lead Research Organisation:
University of Edinburgh
Department Name: Sch of Informatics
Abstract
1) To create the next generation of Natural Language Processing experts, stimulating the growth of NLP in the public and private sectors domestically and internationally. A pool of NLP talent will provide incentives for (existing) companies to expand their operations in the UK and lead to start-ups and new products.
2) To deliver a programme which will have a transformative effect on the students that we train and on the field as a whole, developing future leaders and producing cutting-edge research in both methodology and applications.
3) To give students a firm grounding in the challenge of working with language in a computational setting and its relevance to critical engineering and scientific problems in our modern world. The Centre will also train them in the key programming, engineering, and machine learning skills necessary to solve NLP problems.
4) To attract students from a broad range of backgrounds, including computer science, AI, maths and statistics, linguistics, cognitive science, and psychology and provide an interdisciplinary cohort training approach. The latter involves taught courses, hands-on laboratory projects, research-skills training, and cohort-based activities such as specialist seminars, workshops, and meetups.
5) To train students with awareness of user design, ethics and responsible research in order to design systems that improve user statisfaction, treat users fairly, and increase the uptake of NLP technology across cultures, social groups and languages.
2) To deliver a programme which will have a transformative effect on the students that we train and on the field as a whole, developing future leaders and producing cutting-edge research in both methodology and applications.
3) To give students a firm grounding in the challenge of working with language in a computational setting and its relevance to critical engineering and scientific problems in our modern world. The Centre will also train them in the key programming, engineering, and machine learning skills necessary to solve NLP problems.
4) To attract students from a broad range of backgrounds, including computer science, AI, maths and statistics, linguistics, cognitive science, and psychology and provide an interdisciplinary cohort training approach. The latter involves taught courses, hands-on laboratory projects, research-skills training, and cohort-based activities such as specialist seminars, workshops, and meetups.
5) To train students with awareness of user design, ethics and responsible research in order to design systems that improve user statisfaction, treat users fairly, and increase the uptake of NLP technology across cultures, social groups and languages.
Planned Impact
The demand for NLP practitioners in industry, science, commerce, and the public sector currently outstrips supply. Companies like Google and Amazon are aggressively recruiting well-trained NLP experts, because there are relatively few available. The need for specialist NLP training is also felt in academia. Although the number of PhD applicants in NLP has substantially increased in the past five years, most applicants lack background in one or more areas needed to make immediate impact in NLP research. They are typically experts in one discipline (e.g., maths or computer science) but lack foundations in related disciplines (e.g., linguistics). This narrow focus is at odds with doing research in a multi-disciplinary field like NLP.
The proposed CDT will create the next generation of NLP experts, stimulating the growth of NLP in the public and private sectors in the UK and internationally. A pool of NLP talent will provide incentives for (existing) companies to expand their operations in the UK and lead to start-ups and new products.The University of Edinburgh is number one in the UK for spin-out and start-up creation, having recorded 250 startups and spinouts since 2000, with 47 such companies arising from the School of Informatics in the past six years. We have a rich existing infrastructure to support students in commercializing their ideas, including business training and events for connecting students with potential business partners and investors.
We also expect that the CDT will lead to several innovations in natural language processing (NLP) which in turn will affect the language services sector in a number of important ways. Machine translation, computer-aided translation tools, predictive typing, all rely on advances in NLP. Other examples include digital assistants like Alexa, Siri or Google Home, and applications for media, healthcare, legal services, and education.
The proposed CDT will create the next generation of NLP experts, stimulating the growth of NLP in the public and private sectors in the UK and internationally. A pool of NLP talent will provide incentives for (existing) companies to expand their operations in the UK and lead to start-ups and new products.The University of Edinburgh is number one in the UK for spin-out and start-up creation, having recorded 250 startups and spinouts since 2000, with 47 such companies arising from the School of Informatics in the past six years. We have a rich existing infrastructure to support students in commercializing their ideas, including business training and events for connecting students with potential business partners and investors.
We also expect that the CDT will lead to several innovations in natural language processing (NLP) which in turn will affect the language services sector in a number of important ways. Machine translation, computer-aided translation tools, predictive typing, all rely on advances in NLP. Other examples include digital assistants like Alexa, Siri or Google Home, and applications for media, healthcare, legal services, and education.
Organisations
- University of Edinburgh, United Kingdom (Lead Research Organisation)
- SICSA (Project Partner)
- To Play For Ltd (Project Partner)
- Thomson Reuters Foundation, United Kingdom (Project Partner)
- Toshiba Research Europe Ltd, United Kingdom (Project Partner)
- Facebook (Project Partner)
- nVIDIA, United States (Project Partner)
- Emotech Ltd (Project Partner)
- Fact Mata Ltd (Project Partner)
- British Broadcasting Corporation - BBC, United Kingdom (Project Partner)
- Quorate Technology Ltd (Project Partner)
- Naver Labs Europe (Project Partner)
- dMetrics (Project Partner)
- Mozilla Foundation, United States (Project Partner)
- Amazon Web Services, United States (Project Partner)
- adeptmind (Project Partner)
- CereProc Limited, United Kingdom (Project Partner)
- RASA Technologies GmbH (Project Partner)
- Sertis (Project Partner)
- Microsoft Research Ltd, United Kingdom (Project Partner)
Studentship Projects
Project Reference | Relationship | Related To | Start | End | Student Name |
---|---|---|---|---|---|
EP/S022481/1 | 01/04/2019 | 30/09/2027 | |||
2260597 | Studentship | EP/S022481/1 | 01/09/2019 | 31/08/2023 | Dan Wells |
2263718 | Studentship | EP/S022481/1 | 01/09/2019 | 31/08/2023 | Henry Conklin |
2265467 | Studentship | EP/S022481/1 | 01/09/2019 | 31/08/2023 | Nikita Moghe |
2260413 | Studentship | EP/S022481/1 | 01/09/2019 | 29/02/2024 | Nicole Meng |
2263586 | Studentship | EP/S022481/1 | 01/09/2019 | 31/08/2023 | Irene Winther |
2268062 | Studentship | EP/S022481/1 | 01/09/2019 | 30/11/2023 | Emelie Van de Vreken |
2260385 | Studentship | EP/S022481/1 | 01/09/2019 | 31/08/2023 | Nina markl Markl |
2259958 | Studentship | EP/S022481/1 | 01/09/2019 | 31/08/2023 | Georgia-Ann Carter |
2260349 | Studentship | EP/S022481/1 | 01/09/2019 | 31/01/2024 | Faheem Kirefu |
2265469 | Studentship | EP/S022481/1 | 01/09/2019 | 31/08/2023 | Rohit Saxena |
2263654 | Studentship | EP/S022481/1 | 01/09/2019 | 31/08/2023 | Jie Chi |
2265391 | Studentship | EP/S022481/1 | 01/09/2019 | 31/08/2023 | Parag Jain |
2260410 | Studentship | EP/S022481/1 | 01/09/2019 | 31/08/2023 | Rimvydas Rubavicius |
2259980 | Studentship | EP/S022481/1 | 01/09/2019 | 31/08/2023 | Thomas Hosking |
2258253 | Studentship | EP/S022481/1 | 01/09/2019 | 31/08/2023 | Thomas Hosking |
2265453 | Studentship | EP/S022481/1 | 01/09/2019 | 31/08/2023 | Laurie Burchell |
2265471 | Studentship | EP/S022481/1 | 01/10/2019 | 30/09/2023 | Ronald Cardenas |
2415160 | Studentship | EP/S022481/1 | 01/09/2020 | 31/08/2024 | Radina Dobreva |
2419937 | Studentship | EP/S022481/1 | 01/09/2020 | 31/08/2024 | Agostina Calabrese |
2415176 | Studentship | EP/S022481/1 | 01/09/2020 | 31/08/2024 | Danyang Liu |
2415169 | Studentship | EP/S022481/1 | 01/09/2020 | 30/11/2024 | Martin Hartt |
2417001 | Studentship | EP/S022481/1 | 01/09/2020 | 31/08/2024 | Zheng Zhao |
2435424 | Studentship | EP/S022481/1 | 01/09/2020 | 31/08/2024 | Atli Sigurgeirsson |
2425922 | Studentship | EP/S022481/1 | 01/09/2020 | 31/08/2024 | Siqi Sun |
2415173 | Studentship | EP/S022481/1 | 01/09/2020 | 14/09/2024 | Anil Batra |
2415165 | Studentship | EP/S022481/1 | 01/09/2020 | 31/08/2024 | Lauren Fletcher |
2415166 | Studentship | EP/S022481/1 | 01/09/2020 | 31/08/2024 | Eddie Ungless |
2435337 | Studentship | EP/S022481/1 | 01/09/2020 | 31/08/2024 | Wanqiu Long |
2415171 | Studentship | EP/S022481/1 | 01/09/2020 | 31/08/2024 | Verna Dankers |
2419944 | Studentship | EP/S022481/1 | 01/09/2020 | 31/08/2024 | Matthias Lindemann |
2419933 | Studentship | EP/S022481/1 | 01/09/2020 | 31/08/2024 | Shangmin Guo |