I am a Professor of Machine Learning and AI Strategy Lead at the School of Computer Science, Founding Head of AI Research Engineering at the Centre for Machine Intelligence, and the Turing Academic Lead at the University of Sheffield. I am the lead organiser and founder of the Alan Turing Institute’s interest group on Meta-learning for multimodal data (welcome to sign up and join) and the annual Multimodal AI Workshop and Research Sprint (welcome to subscribe to our Multimodal AI Community mailing list). I lead the development of a course on An Introduction to Transparent Machine Learning, part of the Alan Turing Institute’s online learning courses in responsible AI.

My research focuses on developing translational AI technologies for better analysing multimodal data in healthcare and beyond, particularly multidimensional data and heterogeneous graphs in bioinformatics and medical imaging. I lead the development of the PyKale library to provide more accessible machine learning from multiple sources for interdisciplinary research, officially part of the PyTorch ecosystem.

I serve as an Associate Editor of IEEE Transactions on Neural Networks and Learning Systems, IEEE Transactions on Cognitive and Developmental Systems, and the World Scientific Annual Review of Artificial Intelligence. I served as an area chair of IJCAI2021, and a senior program committee member of IJCAI and AAAI since 2018. I was a recipient of a Turing Network Development Award, an Amazon Research Award, an AAAI Outstanding PC Member Award, a Hong Kong Research Grants Council Early Career Award, an IEEE CIS Outstanding PhD Dissertation Award, and a joint recipient of a Wellcome Trust Innovator Award and an NIHR AI in Health and Care Award. I am a Senior Member of IEEE.

Three of my MSc dissertation students received the Fretwell-Downing Prize for the best MSc Dissertation in their respective years (P. Bai in 2017, H. Xu in 2019, and M. N. I. Suvon in 2022). See the bottom for the whereabouts of my past team members.

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PhD enquiries: Email me ONE PDF including CV, a statement on why and your source of funding, 1-3 papers, and transcripts before applying. Also check the English language requirements.