Project: Process-based flood frequency analysis using storm-tracking
Supervisors: Dr Thomas Kjeldsen and Dr Ilaria Prosdocimi
Andy obtained his first class BSc (Hons) in Computer Science from the University of Plymouth in 2017, where his dissertation focused on the optimisation of genetic algorithms for satisfiability problems such as Ramsey theory. Before this, he conducted a broad range of research including: the use of neural network approaches to model extreme rainfall, the applications of neuroevolution, blockchain architectures for digital voting and finally approaches to peer learning. Current research includes the sentiment analysis of public perception on water restriction measures.
Outside of academia, he has also been an active member of the British Computer Society through taking on various voluntary roles such as the young person representative for the BCS South West branch (present) and chairman of the Plymouth Student Chapter (2015-16).
Throughout his degree, Andy has obtained a large variety of experience in the IT industry. For example, in 2015-2016 during his industrial placement he took on a variety of tasks within HM Land Registry such as development of enterprise scale applications in Python and Java, data and system design production and production of a technical paper on telephony interoperability.
- Application and development of autonomous sensor agents and artificial intelligence approaches to water quality analysis.
- Hydro applications of theoretical computer science (Satisfiability, graph & network theory)