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.

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.

Publications

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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 31/08/2023 Nicole Meng
2263586 Studentship EP/S022481/1 01/09/2019 31/08/2023 Irene Winther
2268062 Studentship EP/S022481/1 01/09/2019 31/08/2023 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 31/10/2023 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