My academic career spans over 20 years of sustained research excellence, interdisciplinary collaboration, and research‑informed educational leadership. Trained as a biomedical scientist, my research portfolio combines internationally recognised disciplinary research with an increasingly influential programme of pedagogic research focused on reducing degree awarding gaps and improving equity of outcomes in higher education.

My disciplinary research has contributed to advances in vascular biology, inflammatory signalling, pharmacology, and computational health analytics. I have authored 39 peer‑reviewed research papers, 9 review articles and a book chapter, and over 2,200 citations (h‑index 22). A defining feature of this work is interdisciplinary collaboration, particularly in the application of computational and AI/ML approaches to real‑world clinical datasets. Notably, I co‑led the development of machine‑learning tools predicting COVID‑19 severity and mortality using routine blood biomarkers, resulting in high‑impact publications, international recognition, a first‑prize hackathon award, and significant public engagement through national and international media. Across my disciplinary work, my approach emphasises methodological rigour, translational relevance, and collaborative problem‑solving.

Alongside this, I have developed a coherent and data‑driven programme of pedagogic research focused on assessment design, curriculum structure, and student success. This work is premised on the principle that degree awarding gaps are shaped by institutional practices rather than student deficit. My recent research evaluated a suite of inclusive assessment interventions in undergraduate Biosciences, including SMART worksheets, laboratory simulations, and transparent rubric‑based marking. Using longitudinal analysis across three academic years and nearly 700 students, this work demonstrated a statistically significant reduction in attainment gaps between students from lower‑ and higher‑income backgrounds at Level 4, narrowing from –6.3% to –1.7%. Similar reductions were observed across ethnic groups, alongside improved likelihood of achieving good honours outcomes.

This research evidences that structural changes to assessment and feedback — without lowering academic standards — can meaningfully improve confidence, continuation, and equity of outcomes. The work was recognised nationally through the LearnSci Teaching Innovation Prize and is now informing wider curriculum reform across the School of Applied Sciences. As Associate Dean (Education and Student Experience), I am uniquely positioned to scale pedagogic research into institutional practice, embedding evidence‑based innovations across more than 30 modules and delivering measurable improvements in continuation, completion, and student satisfaction metrics.

Externally, I contribute to sector‑level leadership through senior roles with the Institute of Biomedical Science, including Chair of the HEI Specialist Advisory Panel and Chair of national academic sessions, alongside external examining at Imperial College London. I am regularly invited to present on inclusive assessment, educational innovation, and equity of outcomes.

Overall, my research profile is defined by coherence across disciplinary science, pedagogic scholarship, and educational leadership. Whether advancing biomedical research or transforming assessment practices to close degree awarding gaps, my work is underpinned by rigorous data analysis, interdisciplinary collaboration, and a commitment to research with clear academic and societal impact.

1. Assessment Design and Degree Awarding Gaps

• Longitudinal, multi‑institutional analysis of how different assessment formats influence awarding gaps
• Causal modelling of assessment transparency, feedback mechanisms, and student outcomes
• Scaling inclusive assessment practices across disciplines

2. Learning Analytics and Student Success

• Predictive modelling of continuation and completion using assessment and engagement data
• Equity‑focused learning analytics: identifying structural rather than behavioural risk factors
• Ethical use of AI in monitoring student engagement and attendance

3. Digital Pedagogies in Laboratory‑Based Disciplines

• Impact of lab simulations and preparatory tools on attainment and confidence
• Differential effects of digital scaffolding across demographic groups
• Blended laboratory models and inclusivity