Dr Phillip Smith PhD, FHEA

Dr Phillip Smith

School of Computer Science
Associate Professor
Head of Education

Contact details

Email
p.smith.7@bham.ac.uk
View my research portal
Address
School of Computer Science
University of Birmingham
Edgbaston
Birmingham
B15 2TT
UK

Phillip Smith is an Associate Professor and Head of Education in the School of Computer Science. His interests span natural language processing, applied artificial intelligence and computing education, including sentiment analysis, generative AI and the design of effective computing curricula.

Qualifications

  • PGCert in Higher Education, University of Birmingham, 2022
  • Fellow of the Higher Education Academy (FHEA)
  • PhD in Computer Science, University of Birmingham, 2017
  • BSc (Hons) Computer Science (First Class), University of Birmingham, 2009

Biography

Phillip Smith graduated with a first-class BSc in Computer Science from University of Birmingham in 2009. After working as a software engineer on an artificial intelligence platform, he returned to Birmingham to undertake doctoral research on machine-learning approaches to sentiment analysis in the clinical domain, receiving his PhD in 2017.

He is now an Associate Professor and Head of Education in the School of Computer Science. He has held a range of educational leadership and student-support roles within the School of Computer Science and works across undergraduate and postgraduate education, curriculum development, assessment and teaching delivery. His teaching spans software engineering, programming and data science, and natural language processing.

Phillip's academic interests sit at the intersection of natural language processing, applied artificial intelligence and computing education. His NLP work includes sentiment and emotion analysis, text summarisation, multilingual and low-resource language processing, and cross-lingual classification. He is also interested in how generative AI is changing the way computing is taught and assessed, and in designing educational approaches that help students develop robust technical and professional skills.

Teaching

  • Software Engineering (undergraduate) - module leadership
  • Natural Language Processing / Natural Language Processing (Extended) (undergraduate and postgraduate)
  • Programming for Data Science (postgraduate)

Postgraduate supervision

Phillip is interested in supervising doctoral research in natural language processing, computational linguistics and applied machine learning. Areas of particular interest include sentiment and emotion analysis, text summarisation, multilingual and low-resource NLP, cross-lingual classification, and the effective and responsible use of large language models. Previous PhD students have worked on parameter adaptation for large language models; multilingual event extraction from social media; online promotional bots; Arabic emoji sentiment; metaphor classification; Arabic affect and offensive-language detection; long-document summarisation; crisis detection from Arabic social media; and virtual reality to support mental health.

Research

Phillip's research focuses on natural language processing and applied artificial intelligence. His work has included sentiment and emotion analysis, text summarisation, low-resource and multilingual NLP, cross-lingual classification, and machine-learning methods for analysing human language. Recent collaborations have included language technologies for Urdu, crisis-related social-media classification, automated assessment of theory of mind, and human-centred applications of AI.

He also has a growing research and scholarship interest in computing education, particularly programming education, student experience, and the implications of generative AI for curriculum design and assessment.

Other activities

Phillip Smith is a careers tutor and an A2B lead tutor for the School of Computer Science. He has also carried out consultancy work for Birmingham City Council on the issue of public health.

Publications

Recent publications

Article

Cremona, L, Dunne, N, Sharma-Oates, A, Smith, P & Compton, L 2025, '“Feeling the code”: Emotions in programming and interventions supporting positivity’', Education in Practice. <https://education-in-practice.co.uk/cremona-et-al-feeling-the-code/>

Ali, M, Baqir, A, Raza Sherazi, HH, Khalid, S, Smith, P & Lee, M 2024, 'An Extended Pattern Based Comprehensive Stemmer for the Urdu Language', ACM Transactions on Asian and Low-Resource Language Information Processing, vol. 23, no. 12, 169. https://doi.org/10.1145/3701231

Devine, RT, Kovatchev, V, Grumley Traynor, I, Smith, P & Lee, M 2023, 'Machine learning and deep learning systems for automated measurement of ‘advanced’ theory of mind: reliability and validity in children and adolescents', Psychological Assessment, vol. 35, no. 2, pp. 165-177. https://doi.org/10.1037/pas0001186

Alharbi, AI, Smith, P & Lee, M 2022, 'Integrating character-level and word-level representation for affect in Arabic tweets', Data and Knowledge Engineering, vol. 138, 101973. https://doi.org/10.1016/j.datak.2021.101973

Conference article

Potts, K, Smith, P & Bahja, M 2024, 'Exploring the Potential of Virtual Reality Sensory Rooms', CEUR Workshop Proceedings, vol. 3712, 4. <https://ceur-ws.org/Vol-3712/paper4.pdf>

Alharbi, AI, Smith, P & Lee, M 2021, 'Enhancing contextualised language models with static character and word embeddings for emotional intensity and sentiment strength detection in Arabic tweets', Procedia CIRP, vol. 189, pp. 258-265. https://doi.org/10.1016/j.procs.2021.05.089

Conference contribution

Al Amer, S, Lee, M & Smith, P 2025, Adopting Ensemble Learning for Cross-lingual Classification of Crisis-related Text On Social Media. in AK Ojha, C Liu, E Vylomova, F Pirinen, J Abbott, J Washington, N Oco, V Malykh, V Logacheva & X Zhao (eds), Proceedings of The Seventh Workshop on Technologies for Machine Translation of Low-Resource Languages (LoResMT 2024). Association for Computational Linguistics, ACL, pp. 159-165, Seventh Workshop on Technologies for Machine Translation of Low-Resource Languages , Bangkok, Thailand, 15/08/24. https://doi.org/10.18653/v1/2024.loresmt-1.16

Al Amer, S, Lee, M & Smith, P 2025, Comparative Evaluation of Machine Translation Models Using Human-Translated Social Media Posts as References: Human-Translated Datasets. in AK Ojha, C Liu, E Vylomova, F Pirinen, J Washington, N Oco & X Zhao (eds), Proceedings of the Eighth Workshop on Technologies for Machine Translation of Low-Resource Languages (LoResMT 2025). Association for Computational Linguistics, ACL, pp. 1-9, The Eighth Workshop on Technologies for Machine Translation of Low-Resource Languages, Albuquerque, New Mexico, United States, 3/05/25. https://doi.org/10.18653/v1/2025.loresmt-1.1

Potts, K, Smith, P & Bahja, M 2025, Virtual Reality Sensory Rooms: A Tool to Reduce Anxiety in Autistic Adults. in TZ Ahram & R Motschnig (eds), Human Interaction and Emerging Technologies (IHIET 2025): Proceedings of the 15th International Conference on Human Interaction & Emerging Technologies (IHET 2025) August 25-27, 2025, University of Vienna, Austria. Open Access Science in Human Factors Engineering and Human Centred Computing, vol. 197, Applied Human Factors and Ergonomics (AHFE) International, pp. 262-271, 15th International Conference on Human Interaction and Emerging Technologies, Vienna, Austria, 25/08/25. https://doi.org/10.54941/ahfe1006719

Alnafesah, G, Smith, P & Lee, M 2023, Are you not moved? Incorporating Sensorimotor Knowledge to Improve Metaphor Detection. in R Mitkov & G Angelova (eds), Proceedings of the 14th International Conference on Recent Advances in Natural Language Processing. International Conference Recent Advances in Natural Language Processing, Incoma Ltd, pp. 80-89, 2023 International Conference Recent Advances in Natural Language Processing: Large Language Models for Natural Language Processing, RANLP 2023, Varna, Bulgaria, 4/09/23. https://doi.org/10.26615/978-954-452-092-2_009

Al Amer, S, Lee, M & Smith, P 2023, Cross-lingual Classification of Crisis-related Tweets Using Machine Translation. in R Mitkov & G Angelova (eds), Proceedings of the 14th International Conference on Recent Advances in Natural Language Processing. International Conference Recent Advances in Natural Language Processing, Incoma Ltd, pp. 22-31, 2023 International Conference Recent Advances in Natural Language Processing: Large Language Models for Natural Language Processing, RANLP 2023, Varna, Bulgaria, 4/09/23. https://doi.org/10.26615/978-954-452-092-2_003

Gokhan, T, Smith, P & Lee, M 2023, Node-Weighted Centrality Ranking for Unsupervised Long Document Summarization. in E Métais, F Meziane, V Sugumaran, W Manning & S Reiff-Marganiec (eds), Natural Language Processing and Information Systems: 28th International Conference on Applications of Natural Language to Information Systems, NLDB 2023, Derby, UK, June 21–23, 2023, Proceedings. 1 edn, Lecture Notes in Computer Science, vol. 13913, Springer, Cham, pp. 299–312, 28th International Conference on Applications of Natural Language to Information Systems, Derby, United Kingdom, 21/06/23. https://doi.org/10.1007/978-3-031-35320-8_21

Kovatchev, V, Smith, P, Lee, M & Devine, R 2021, Can vectors read minds better than experts? Comparing data augmentation strategies for the automated scoring of children's mindreading ability. in C Zong, F Xia, W Li & R Navigli (eds), Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers). vol. 1, International Joint Conference on Natural Language Processing (IJCNLP), Association for Computational Linguistics, ACL, pp. 1196-1206, Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, ACL-IJCNLP 2021, Virtual, Online, 1/08/21. https://doi.org/10.18653/v1/2021.acl-long.96

Gokhan, T, Smith, P & Lee, M 2021, Extractive financial narrative summarisation using SentenceBERT-based clustering. in Proceedings of the 3rd Financial Narrative Processing Workshop FNP 2021., 18, Workshop on Financial Narrative Processing (FNP), Association for Computational Linguistics, ACL, pp. 94-98, 3rd Financial Narrative Processing Workshop, FNP 2021, Lancaster, United Kingdom, 15/09/21. <https://aclanthology.org/2021.fnp-1.18.pdf>

Preprint

Kovatchev, V, Smith, P, Lee, M & Devine, R 2021 'Can vectors read minds better than experts? Comparing data augmentation strategies for the automated scoring of children's mindreading ability' arXiv, pp. 1-11. <https://arxiv.org/abs/2106.01635v1>

View all publications in research portal

Expertise

Artificial intelligence; natural language processing; large language models and generative AI; computing education and assessment.