Dr George De Ath
I am part of Project Bluebird, a prosperity partnership programme between the University of Exeter, NATS and The Alan Turing Institute. My role is to develop novel machine learning, optimisation and control algorithms for air traffic control. In particular, I am focused on developing algorithms which can safely, dynamically, and efficiently control air traffic in real-world scenarios, while addressing the challenges of robust multi-objective optimisation in dynamic airspace environments.
Previously, I was a permanent Research Fellow for the Institute for Data Science and Artificial Intelligence (IDSAI) at the University of Exeter. Between 2019 and 2021 I worked as a Postdoctoral Research Fellow on two UKRI-funded projects, RIBA to Reality: Deep Digital Twin to enable Human-Centric Buildings for a Carbon Neutral Future and Rapid Calibration for Operational and Strategic Digital Twins. Prior to this, I obtained my MSci in Computer Science and Mathematics and my Ph.D. in Computer Science, both at the University of Exeter.
My main research interests include the optimisation (calibration) of expensive-to-evaluate problems (models) using Bayesian optimisation, as well as more general single- and multi-objective optimisation tasks, and solving regression/classification problems in machine learning. I have experience in evolutionary optimisation, probabalistic modelling, with a particular focus on Gaussian processes, uncertainty quantification, and general machine learning methods, e.g., (convolutional) neural networks, random forests, support vector machines, etc.
I am happy to supervise Ph.D. students, particually those with interests in Bayesian optimisation and machine learning using both traditional statistical methods (i.e., Gaussian processes) and deep learning-based methods.