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Photo of Mr Charlie Kirkwood

Mr Charlie Kirkwood

Postgraduate

Email:

Telephone: 01392 726403

Extension: (Streatham) 6403

I'm a scientist with a keen interest in statistical methods and computational technology. I believe that statistical modelling, machine learning, and artificial intelligence (under any name) will become increasingly important in the future of our society. Already these tools are allowing us to better understand the world we live in and the systems we interact with, meaning better decisions can be made - and these abilities will only improve. Within this progression is a tension between top-down and bottom-up design - should we instill our beliefs about the world into our decision making tools, or allow these tools to decipher the complexities of the world for themselves, with the potential to learn beyond what we thought we knew?

I'm currently a postgraduate researcher on an EPSRC and Met Office CASE funded PhD studentship entitled 'Using cutting edge statistical and data science techniques to optimise and improve weather forecasts' - the project aims to develop a hybrid approach combining top-down numerical weather prediction models and bottom-up statistical learning to generate more accurate probabilistic weather forecasts.

Prior to starting my PhD, I originally graduated with a masters degree in Exploration and Resource Geology from Cardiff University and started out working in the mineral exploration industry, where geostatistical methods are a key part of decision making. I then moved into a NERC funded research position at the British Geological Survey where I developed more advanced statistical and machine learning methods for quantitative geological mapping (see publications, and website). Keen to pursue my quantitative interests beyond the boundaries of geology, I later took a job as a commercial data scientist at Walgreens Boots Alliance (parent company of Boots on the UK high street), where I developed machine learning methods to improve personalised targeting of offers to customers, and natural language processing systems for prioritising responses to customer feedback.

Grants and Awards:

2018 - Exeter University Researcher-Led Initiative grant, which I used to co-organise two courses - 'An introduction to the Git ecosystem for version control and code sharing' and 'An introduction to data analysis in Python', both kindly taught by Dr Chris Woods, Research Software Engineering Lead at the University of Bristol.

2018 - WBA Global Brands 'Makers' award, for advancing data science at Boots UK.

2017 - Elsevier Outstanding Reviewer award for my contributions to the Journal of Geochemical Exploration.

2016 - NVIDIA GPU grant, awarded a Titan X Pascal GPU to accelerate research into the use of neural networks & deep learning in geological mapping and mineral exploration (for example see poster here).