Sammi Rosser

Expertise

Mental health, health data science

Biography

I am a Postdoctoral Research Fellow with an interest in making data science and operational research techniques more accessible to the organisations that can benefit from them the most. My role in the ARC is as a trainer and mentor on the HSMA programme (www.hsma.co.uk), which trains health and social care staff to use data science and operational research techniques in their organisations. 

My research focuses on making computational approaches to healthcare decision-making easier to apply, particularly in discrete event simulation, geographic optimisation, mapping and web applications. This includes developing Python tools and workflows that make established techniques more accessible to beginner programmers and healthcare practitioners. I design bespoke content and teach in these areas on the HSMA programme, as well as teaching introductory Python programming and supervised machine learning. My Python packages include the vidigi package for open source simulation animation (https://hsma-tools.github.io/vidigi/vidigi_docs/) and the lokigi package for equity-aware multi-objective site location optimisation problems (https://hsma-tools.github.io/lokigi/lokigi_docs/). 

I am also the co-author of several eBooks in health data science and operational research, freely available via our HSMA books page (www.hsma.co.uk/books). They are designed to be accessible to beginners while providing useful reference material for more experienced practitioners. 

I am keen to promote the reuse of solutions across the healthcare space, and I am the creator and primary curator of the Healthcare Services Analytics & Decision Science Atlas (https://atlas.hsma.co.uk/), which catalogues projects, tools, training, techniques and graphs of use in this area. 

Before joining PenCHORD, I completed an MSc in Health Data Science at the University of Exeter and worked as a Data Scientist at Devon Partnership Trust, where I collaborated with PenCHORD to identify opportunities for the application of data science and operational research to improve urgent and inpatient mental health care. Better use of data in mental health services remains an area of interest to me.