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.

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.