My work at Bournemouth University focuses on the development of at-scale statistical approaches for the analysis of health & social sciences data for several application domains key to these sectors. My interests are in quantitative methods for causal inference using large datasets, inverse problems in imaging, time-series analysis and system dynamics/systems thinking approaches for the analysis of large complex healthcare systems.

Prior to my role at Bournemouth, I was Technical Lead/Senior Data Scientist at Siemens Healthineers, Erlangen Germany within the Magnetic Resonance (MR) Imaging Business Line. In this role I developed Business Analytic hypotheses and supporting quantitative statistical models for new lines of digital services & products in the domains of operational analytics for clinical workflows, clinical decision-making in radiology, and predictive maintenance of the MR system global fleet.

Before taking the role at Siemens, I spent four years as a Research Scientist (staff scientist track) at the Massachusetts Institute of Technology, Sloan School of Management, Cambridge, USA where I worked on an IARPA(Intelligence Advanced Research Projects Agency)-funded program focussed on next generation elicitation using Bayesian methodology for expert forecasting in several arenas including economics, finance, politics and security scenarios... While at MIT, in a separate project I worked at the interface between neuroscience and economics as an investigator on a Bank of Japan-funded program on quantitative methods to model the underlying neural signatures of trust when making investment decisions.

Prior to MIT I worked on imaging problems in the pharmaceutical industry and academia as a Lecturer (Assistant Professor) in Imaging Sciences at Imperial College London and trained for four years as a Senior Research Fellow at Harvard University in Biomedical Imaging (in the lab of Professor Emery Brown). In these periods, I developed statistical and timeseries models applying those to the domain of (f)MRI/MEG neuroimaging and nonstationary neuroscientific timeseries data.