Program Lead, Machine Learning and Biomedical Informatics
I lead the Machine Learning and Biomedical Informatics program at The George Institute, The University of Oxford (part of Oxford Martin School) and am the Head of Quantitative Analytics, EMEA and Special Projects Lab with AIG. I also holds an adjunct fellowship with The University of Oxford's Centre for Functional MRI of the Brain (FMRIB), and am a principal scientist with the Human Connectome Project (an ambitious attempt to pinpoint the brain’s information-processing principals/networks).
My interests include biomedical informatics (e.g., neuroinformatics and medical imaging), healthcare (e.g., technology-enabled delivery of care, and decision-support systems), machine learning (e.g., deep learning, representation learning, Bayesian statistics, computer vision, and network inference), and big data technologies (Spark and high-performance computing platforms) in finance and biomedicine.
Usual blood pressure, atrial fibrillation and vascular risk: evidence from 4.3 million adults
Emdin CA. et al, (2016), International Journal of Epidemiology, dyw053 - dyw053
Usual blood pressure, peripheral arterial disease, and vascular risk: cohort study of 4.2 million adults.
Emdin CA. et al, (2015), BMJ, 351
Usual blood pressure and risk of vascular dementia
Emdin CA. et al, (2015), EUROPEAN HEART JOURNAL, 36, 987 - 988
Functional connectivity in the basal ganglia network differentiates PD patients from controls.
Szewczyk-Krolikowski K. et al, (2014), Neurology, 83, 208 - 214
Study protocol: the Whitehall II imaging sub-study
Ebmeier KP., (2014), BMC Psychiatry, 1