Dr Neil Caithness is a Senior Researcher at the e-Research Centre.
Neil's primary research revolves around solving data science problems and implementing elegant solutions in R and Matlab. Implementations are either reusable code packages, or fully functional user applications. Neil has special expertise in unsupervised, high-dimensional machine learning (discovery), and supervised learning and validation (classification, regression).
With a long history of collaborating across both academic and business partnerships, Neil has been the lead data scientist on diverse projects including:
(Most recent first)
DIET - In collaboration with British Gas and funded by Innovate UK, the lead data scientist on a project that aims to detect energy theft from smart meter data using advanced machine learning techniques. The technical method developed for this project has been filed through Oxford University Innovation as British patent application 1713703.5.
Stategic Blue KTP - Mentor for the KTP associate in data science at Strategic Blue.
CLOUDWATCH - Funded by the European Commission, analysed the relationships among the EC's portfolio of cloud computing projects. This work was published in the Journal of Cloud Computing (https://doi.org/10.1186/s13677-017-0084-1).
INFORM - In collaboration with the Global Canopy Program and the European Forest Institute developed a program to trace the impact of commercial supply chains on Amazonian deforestation. A paper has been submitted for review to PLOS ONE.
LEFT - In collaboration with Oxford's Zoology Department implemented the Local Ecological Footprint Tool used to asses the impact of mining explorations. This work resulted in several publications.
VIBRANT - In collaboration with the Natural History Museum, London, led the data science and cloud computing initiatives to build a virtual biodiversity laboratory.
Read a Q&A with Dr Caithness.