Position: Senior Research Fellow in the Leeds Institute of Health Sciences, School of Medicine
Expertise: health data science; electronic healthcare records; applied health research; prognostic models; statistical modelling; machine learning; parallel computing; linear algebra; numerical analysis
Research Interests: I'm interested in the application of cutting-edge statistical/AI methodologies to healthcare data, and particularly electronic healthcare records. This allows for the best possible solution to clinical research questions to be addressed using the large-scale healthcare data that is increasingly available for research from NHS Digital, CPRD, etc. This is particularly useful for questions where a clinical trial is infeasible or impossible. I am involved in a number of NIHR-funded projects across a wide variety of clinical areas including geriatrics (updating the electronic frailty index), mental health (investigating effect of service provision on re-attendance at the hospital), and musculoskeletal conditions. Previously I worked on batch linear algebra algorithms to dramatically improve the speed of, amongst other things, low-level operations required in modern machine learning software. These algorithms are currently used by NVIDIA, Intel, and ARM.