Andy Barnes

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).

Work Experience

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.

During the final year of his degree, Andy worked for the Plymouth Allied Health Center on the production of various simulation utilities in R, Matlab and Python. After completing this he returned to software engineering, taking a role at the British Computer Society as a software engineer, tasked with developing large-scale applications in C# and Javascript utilizing cloud based technologies such as AWS and Google Cloud. He is now an associate lecturer at the University of Plymouth for the module involving enterprise architecture and distributed systems.

Research Interests

  • 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)