Areas of expertise
- Aeronautical Systems
Danny is an experienced software engineer and IT professional, having spent 17 years supporting the Royal Air Force's E-3D Sentry aircraft’s mission system software, whilst serving for a total of 22 years. Their first five years in the RAF saw them first working as an electrician on Jaguar and later Harrier aircraft.
Their move to an IT role was sparked by a lifelong love of computing and starting a part-time BEng degree with the Open University. Having played a lead role in producing critical software upgrades to the Sentry platform, Danny gained Charted IT professional and Incorporated Engineer status through the British Computer Society. After this achievement, more OU study followed gaining PGCert in technology management in 2014 before undertaking an MSc in cyber defence and information assurance with Cranfield Defence and Security. Graduating in 2020, Danny completed their final year in the RAF applying their newly found cyber knowledge but deciding that their future lay in research.
Danny is conducting research into explainable artificial intelligence for air traffic management. The research is of interest to them due to their background working with the Sentry’s mission system and due to the work that they carried out for their MSc thesis which was titled “Concept drift in machine learning algorithms trained to detect unknown malware.” The project contrasts heavily with Sentry’s equipment that was based on technology from the 1970s and 80s.
Danny aims to produce a deep learning classifier that can classify targets detected by a primary surveillance radar and enable the algorithm to explain how or why it made the classification. The classifier will aid aircraft and airport safety by combining the capability of counter UAV systems with the traditional surveillance radars. Explainability is an important property in safety critical systems such as air traffic management, as it helps to build trust in machines that will make decisions rather than supporting humans to make decisions. Once the XAI classifier has been built and its performance assessed, research into how the system can be verified, validated, and certified will be undertaken.
The research project is sponsored by Saab Technologies and will be undertaken in the Digital Aviation Research and Technology Centre DARTeC at the Cranfield Campus.