Professor Eric Atwell

Professor Eric Atwell


My research speciality is Artificial Intelligence for Language research: AI applied in corpus linguistics and text analytics: Machine Learning and Data Mining analysis of a CORPUS of text - in English, Arabic, or other languages - to analyse the text and detect "interesting" and "useful" features or patterns. For example:

  • Understanding religious texts such as the Quran, to find links and patterns in the Quran verses and chapters whcih are of interest to religious scholars and the general public.
  • Detecting terrorist activities, by analysis of documents from terrorist suspects, to highlight suspicious parts of the text.
  • AI intelligent personal assistants for university students or lecturers, to advise students on courses, or write exam questions and answers from lecture transcripts, 
  • Detecting cause of death from verbal autopsy text documents describing the circumstances of the death.

I have led research projects, including EPSRC-funded project Natural language processing working together with Arabic and Islamic Studies , EPSRC/ESRC/CPNI-funded research project IDEAS factory - detecting terrorist activities: making sense , JISC-funded project e-Health GATEwayto the Clouds , HEA-funded project web-based resources for teaching and research in Islamic Studies .

I work with the Artificial Intelligence Research Theme and and LIDA Leeds Institute for Data Analytics

I am proud of over 60 research students and Research Fellows I have supervised, who went on to work in a range of careers, including web search, banking and finance, text analytics, translation and language consulting, online news, voice-to-text, the search for extra-terrestrial intelligence, and university researchers and professors..

I live with my family and pets. 

Academic responsibilities: Director of Research PostGraduate Studies, Programme Leader for development of new online MSc in AI; plus: TEACHING: COMP2121 Data Mining 172 students), COMP5840M Data Mining and Text Analytics (230 students), XJCO2121 Data Mining (73 students), LISS1031 Data Mining and Text Analytics (20 students), OCOM5204 Data Mining and Text Analytics (new module development for new online MSc in AI) 12 BSc and MSc student research projects, 32 personal tutees; RESEARCH: Supervision: 10 PhD students, 2 Research Fellows; PLUS: writing publications, research project proposals etc; Peer Review College for AHRC, EPSRC, Qatar-QNRF, HongKong-RGC, Irish-RC, Poland-NCRD, EU-H2020; PhD and MSc external examiner; journal and conference reviewer; Arabic-L and AI4L research networks administrator.

Way to go, Eric!

With 1,532 new reads, your research items were the most read research items from your institution

Achieved on 

Gallup STRENGTHSFINDER found my top strengths are:  Learner, Achiever, Ideation, Intellection, Maximizer: I like learning, achieving, ideas, thinking, and excellence.

deepmoji generates emojis for any English text; here are emojis for “Eric Atwell”: analysis of "Eric Atwell" analysis of "Eric Atwell"

Previous academic responsibilities

2013 - 2017: Associate Professor, U of Leeds: Research, Teaching within AI group
1996 - 2013: Senior Lecturer, U of Leeds: Research, Teaching, NLP group leader
1994 - 1996: Director, JISC CALAS NTI: JISC UK R&D programme leader
1991 - 1994: National Coordinator, JISC KBSI: JISC UK R&D programme leader
1990 - 1991: SERC Advanced Research Fellow: SERC/MoD network coordinator
1984 - 1990: Lecturer, U of Leeds: Teaching, Research, leading NLP within AI team
1981 - 1984: Research Associate, University of Lancaster: Research, grant applications

Research Grants: Investigator

  • EDUBOTS chatbots for university education (ERASMUS+ £94K, 2019-2021)
  • FoodShock 2020 (Science and Technology Facilities Council, £8K, 2020-2021)
  • Artificial Intelligence Networking (Leeds University Academic Development Fund, £2K, 2017)
  • Natural Language Processing Working Together With Arabic And Islamic Studies (Engineering and Physical Science Research Council, £337K, 2013-2015)
  • Web-based resources for Islamic Studies (Higher Education Academy, £13K, 2011)
  • Detecting Terrorist Activities: Making Sense (Engineering and Physical Science Research Council, £2185K (£195K Leeds), 2010-2013)
  • Copying-Identifier for Biomedical Science Reports (Higher Education Funding Council, £60K, 2002)
  • ISLE - Interactive Spoken Language Education (European Union, £720K (£64K Leeds), 1998-2001)
  • Information extraction from air traffic control (Visionair International, £21K, 1994-1997)
  • Mapping between corpus annotation schemes (Nuffield Foundation, £6K, 1994)    
  • Computer based resources in KBS & SALT (Higher Education Funding Council, £92K, 1994-1996)
  • Knowledge based timetable information (Higher Education Funding Council, £39K, 1994-1995)
  • Mapping AMALGAM corpus (Science and Engineering Research Council, £176K, 1993-1997)
  • Computer analysis of language and speech (Higher Education Funding Council, £79K, 1993-1995)
  • Pilot project for CCALAS (Leeds University Research Support, £20K, 1993-1994)
  • A speech-oriented stochastic parser (Ministry of Defence, £178K, 1992-1993)
  • Knowledge-Based Systems Initiative (Joint Information Systems Committee, £149K, 1991-1994)
  • Neural network parsers trained with realistic corpora (British Telecom, £10K, 1990-1991)
  • Advanced Fellowship in IT (Science and Engineering Research Council, £220K, 1990-1994)
  • COMMUNAL Convivial man machine understanding (Ministry of Defence, £83K, 1987-1989)


  • Cancer patient records analysis (PinPoint, £52K, 2019-2020)
  • e-Health GATEway to the Clouds (Joint Information Systems Committee, £52K, 2012)
  • ABC Arabic By Computer (British Society for Middle Eastern Studies, £26K, 1989-1990)
  • A simulated annealing parser for authentic English (Ministry of Defence, £117K, 1986-1989)

PhD research supervision

  • M Aleedy, due 2024, Chat and chatbots for university education
  • A Alsaleh, due 2024, Semantic similarity in Arabic text understanding
  • Z Almugbel, due 2023, English and Arabic medical patient information leaflets
  • S Altammami, due 2022, Parallel corpus and knowledge-base for Islamic Hadith
  • T Tarmom, due 2022, Classifying Arabic Hadith
  • M Alshammeri, due 2022, Deep learning and distributional semantics for the Quran
  • M Alamr, due 2022, Authorship Attribution and Online Identity in Najdi Arabic Tweets
  • J Alasamari, due 2021, Arabic and English verb systems in the Quran corpus
  • N Ahmad, due 2021, Malay natural language processing for retrieval from Malay Qur'an
  • A Alshutayri, 2019, Arabic dialects classification
  • L Aldhubayi, 2019, Corpus-based methods and to extend Arabic WordNet
  • A Alghamdi, 2018, Arabic corpus-informed lexicon of formulaic sequences
  • M Alqahtani, 2019, Quranic Arabic semantic search tool based on ontology of concepts
  • A Alosaimi, 2018, Ensemble morphosyntactic analyser for classical Arabic
  • S Alrehaili, 2018, Ontology concept and relation learning from the Qur’an corpus
  • J Jaafar, 2018, Data mining and machine learning to predict acute coronary illness
  • A Alfaifi, 2016, Arabic learner corpus and a system for Arabic error annotation
  • S Danso, 2016, Text analytics to predict time and cause of death from verbal autopsies
  • K Dukes, 2013, Statistical parsing by machine learning from a Classical Arabic treebank
  • S Hina, 2013, Semantic tagging of medical narratives using SNOMED CT
  • A Muhammad, 2012, Annotation of conceptual co-reference and similarity in the Qur'an
  • J Washtell, 2011, Distributional meaning in text: distance, expectation, and composition
  • M Sawalha, 2011, Open-source resources and standards for Arabic word structure analysis
  • C Brierley, 2011, Prosody resources for automated phrase break prediction
  • O Nancarrow, 2011, Tagging of adverbs in modern English corpora
  • F Su, 2010, Computational modelling of word sense sentiment
  • N Abbas, 2009, Qurany 'Search for a Concept' tool and website
  • A Roberts, 2008, Unsupervised machine learning for grammatical inference
  • D Elliott, 2006, Corpus-based machine translation evaluation via automated error detection
  • B AbuShawar, 2005, A corpus based approach to generalise a chatbot system
  • L Al-Sulaiti, 2004, Designing and developing a Corpus of Contemporary Arabic
  • T Oba, 2003, HTK to analyse prosody in the ISLE corpus of spoken learner's English
  • J Elliott, 2003, Natural language learning for SETI Search for Extra-Terrestrial Intelligence
  • X Duan, 2001, Lexical Semantic Association Between Web Documents
  • G Churcher, 1997, Speech dialogue analysis using linguistic knowledge
  • G Demetriou, 1997, Lexical semantics for human-computer speech communication.
  • M Schillo, 1996, Working while driving: corpus-based in-car personal assistant
  • X Zhang, 1996, MIRTH Chinese and English search engine: a multilingual retrieval tool
  • C Souter, 1996, A corpus-trained parser for systemic-functional syntax
  • A Bull, 1996, Aerobic dance exercise: a corpus-based computational linguistics approach
  • U Jost, 1994, Probabilistic language modeling for speech recognition
  • S Arnfield, 1994, Prosody and syntax in corpus-based analysis of spoken English
  • J Hughes, 1993, Automatically acquiring a classification of words
  • T O’Donoghue, 1993, Reversing the process of generation in Systemic Grammar

Academic visits away from the University of Leeds

2018-2021: visiting professor, Leeds-SWJTU Joint School, SWJT University, Chengdu
2013 - 2017: visiting scholar, SUSTECH Sudan Uni of Science and Technology, Khartoum  
2012 - 2013: visiting scholar, Linguistics and English Language Dept, University of Manchester
2011 -2013: visiting scholar, Computing Dept, King Saud University, Riyadh, Saudi Arabia
2000: visiting scholar, Dept of Computer Science, University of Sheffield  
1994 - 1996: JISC Computer Analysis of Language And Speech New Technologies Initiative
1995: visiting scholar, Dept of Computer Applications, Dublin City University
1994: visiting scholar, Inst for Language & Artificial Intelligence, Tilburg University  
1991 - 1994: National Coordinator, JISC Knowledge Based Systems Initiative
1990 - 1991: Science and Engineering Research Council, Advanced Research Fellowship
1989: visiting scholar, Max Planck Institute and Dept of Language, Nijmegen University


  • Director of Research Postgraduate Studies
  • Online Distance Learning ODL MSc Artificial Intelligence programme leader
  • Artificial Intelligence for Language research leader

Research interests

I lead the AI4L Artificial Intelligence for Language research group:

 Noorhan Abbas, EDUBOTS: chatbots in higher education

 Nor Diana Ahmad, Semantic modelling of Malay translated Qur'an

Nawaf Alajlani, AI Personal Assistant for autistic and dyslexic academics

 Mashael Alamr, Authorship in a corpus of Najdi Arabic tweets

Albatool Alamri, Cross-Lingual Computational Stylometry 

Bader Alanazi, Software Bug Detection by Learning from Code Examples

 Jawharah Alasmari, Arabic and English verb system in the Qur’an Arabic Corpus

 Moneerh Aleedy, English and Arabic chatbots in higher education

 Zainab Almugbel, English and Arabic medical patient information leaflets

 Abdullah Alsaleh,Semantic similarities between Arabic texts

Alaa Alsaqer, Extending WEKA with deep learning for text understanding

Ibtisam Alshammari, Quran knowledge base linking Quran analyses and ontologies

 Menwa Alshammeri, Deep learning distributional semantics for the Arabic Quran

Shatha Altammami,  Parallel corpus and knowledge base for Arabic Hadith

Saud Althabiti, Detecting fake news in Arabic social media

Manar Bageis, Natural language processing for Arabic social media analysis

Claire Brierley, NLP working together with Arabic and Islamic Studies.

Thomas Pickard, EDUBOTS: chatbots in higher education

Taghreed Tarmom. Classifying Arabic Hadith

We are part of the Artificial Intelligence research theme of the School of Computing at the University of Leeds.

<h4>Research projects</h4> <p>Any research projects I'm currently working on will be listed below. Our list of all <a href="">research projects</a> allows you to view and search the full list of projects in the faculty.</p>


  • PhD (Leeds) Corpus linguistics and language learning, 2008
  • BA 1st Class (Lancaster) Computing and Linguistics, 1981

Professional memberships

  • EPSRC (Engineering and Physical Science Research Council) Peer Review College
  • AHRC (Arts and Humanties Research Council) Peer Review College

Student education

My teaching includes: supervision of PhD, MSc, MEng and BSc student research projects; lecturing to Computing MSc, MEng and BSc students; and personal tutorials for students. I have also taught at international conference tutorials and summer schools, for example Aston Summer School on Corpus Linguistics, and Leeds International Summer School.

I have taught a range of subjects, including Corpus Linguistics, Data Mining, Text Analytics, Language, Natural Language Processing, Computational Linguistics, Knowledge Management and Adaptive Systems, Technologies for Knowledge Management, Object Oriented Programming, Professional Development, Knowledge Based Systems, Knowledge Discovery, Perceptual Systems, Future Directions in Distributed Multimedia Systems, Introductory Programming, Numerical Methods, Artificial Intelligence, Databases and Information Systems, Arabic Natural Language Processing, Java, Python, Prolog, Pascal.

Student feedback:
He is a fantastic lecturer who has made the semester significantly more enjoyable with his live lectures. With two semesters which were otherwise ruined by covid-19, COMP2121 was genuinely enjoyable to watch. Plus he has a lovely kitten which made some guest appearances in lecture, which alone should qualify him for an award.”
“i love the commitment and enthusiasm of the module leader Eric Atwell”
“The module leader was lovely and so was his kitten. The coursework was interesting and the group work was helpful. There were a lot of learning materials provided”
He has been really supportive and understanding  during this unprecedented time. Also he helps his students develop other soft skills in addition to their intellectual development.”
“The content was interesting and the lecturer was engaged with the topic”
“I highly recommend this course. The class content of this course is rich, and the teaching methods are diversified, which can well apply the theory to practice”
He is supportive and encourage me every step of the way”
“I learnt a lot from you, many thanks for your regular excellent supervision, caring, and the considerable advices you provided to me, patiently listened to me in meetings, and gave me the best suggestions. Thank you for your endless help, support and guidance.”
“Liked the videos Eric would play before the lecture started on Friday mornings!”
Eric has made me feel like I am attending lectures to learn and not just to pass an exam. When other areas of our course have got tough he has postponed exams and tried to make them as doable as possible for his students. He also makes regular contact with his students and is good at what he does.”
“I thought that the content taught in the module was interesting and engaging, and we were provided with lots of supplementary papers and resources to support our learning”
“Thank you, because you had been a great master for me. A teacher who does not tire of my questions, Support when facing problems, and full of patience.”
Professor Eric is very cooperative with his students and is always available to assist them and answer their inquiries. He always tries to involve them in research groups and reading groups to expand their knowledge. Also, he is committed to time and meeting schedules.”
“Eric is very clearly passionate about the subject, and that's something that always shines through to students. He's an engaging teacher and is more than happy to help with any questions”
“Liked that the module contained a high percentage of coursework content (rather than just exams).”
Eric Atwell has been very supportive of my PhD studies since the start of my journey. He pushed me to read papers and experiment with models, and then publish papers once I successfully finish with experiments. He also reviews my draft papers and reports that the faculty is required me to submit. Eric has also been in contact to his students in regards to finding opportunities to grow as a researcher. Finally, he has never missed or cancelled any meetings throughout my journey which is something that tells me that he is with me along the way.”
“Lecture content was interesting and well presented”
“The teacher fully integrates his own research with the curriculum, and exercises the students' teamwork ability”
I've always enjoyed Eric's lectures because he seemed to genuinely want us to enjoy his module and learn from it. He also put effort in to reduce our stress and be able to actually enjoy the module and want to work for it, opposed to just pass a test.”
“The content was interesting and the professor was really nice and enthusiastic”
“really amiable lecturer, really easy to understand lecturer”
“Nice that there's lots of hands-on/demonstration of material and approaches”
“Enjoyed it as it provided a range of academic enlightenment in the field”
“The teaching method was really impressive, professor also introduced some of the new research ongoing in this field.”


Research groups and institutes

  • Computing in Biology, Medicine and Health
  • Computing in Biology, Medicine and Health
  • Artificial Intelligence
  • Artificial Intelligence

Current postgraduate researchers

<h4>Postgraduate research opportunities</h4> <p>We welcome enquiries from motivated and qualified applicants from all around the world who are interested in PhD study. Our <a href="">research opportunities</a> allow you to search for projects and scholarships.</p>
    <li><a href="//">AI-Dialect: Social media corpus resources for minority language varieties and dialects</a></li> <li><a href="//">AI-Digital Assessment: Machine Learning of exam questions and answers from lecture transcripts</a></li> <li><a href="//,-research-and-services">AI-Edubots: Intelligent Personal Assistants for university teaching, research and services</a></li> <li><a href="//,-word-embedding-models,-and-ontology-terms">AI-MWE: Multi-Word Expressions, word-embedding models, and ontology terms</a></li> <li><a href="//">AI-ReligiousTexts: AI knowledge resources for understanding religious texts</a></li> <li><a href="//">AI-WEKA: extending WEKA with deep learning text understanding</a></li>