Research Associate & Lecturer·PhD Student in Computer Science
Working at the intersection of artificial intelligence and biology, developing multimodal deep learning for single-cell and biomedical data.
I am a Research Associate and part-time Lecturer in the School of Computing, Engineering and Digital Technologies at Teesside University, where I am also pursuing a PhD in Computer Science. My research sits at the intersection of artificial intelligence and biology: I develop multimodal deep learning methods to understand cell fate decisions and cell reprogramming from single-cell and biomedical imaging data, with an emphasis on explainable models.
I also teach and supervise student research projects in the School of Computing, Engineering and Digital Technologies. Before moving into academia, I spent nearly a decade as a business analyst, leading analysis and software-design teams that turned business processes into working software.
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School of Computing, Engineering and Digital Technologies (SCEDT).
School of Computing, Engineering and Digital Technologies (SCEDT).
Led the business analysis and software design teams.
Business process analysis and design of software solutions.
Business analysis and requirements gathering.
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Professional training certificates (LPIC-1, LPIC-2 and more)
Participated in and delivered a workshop at the Net4Brain Training School on Mathematical and Computational Biology of Brain Tumours.
Started as a Research Associate at Teesside University.
Peer review for a manuscript in Springer Nature's Machine Learning journal.
Bridging modalities with AI: a review of AI advances in multimodal biomedical imaging
28th International Conference on Discovery Science (DS 2025).
Unlocking cell fate decisions with multi-modal deep learning
Teesside University
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Health Data Research UK
Transforming patient care and clinical practice
Teesside University