Overview

I am part of Project Bluebird, a prosperity partnership programme between the University of Exeter, NATS and The Alan Turing Institute. I lead the development of novel optimisation-based control algorithms for safe and efficient air traffic control. Following a successful presentation at the British Science Festival, our work was recently featured in the Financial Times.

Previously, I served as 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.

Research Interests

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, probabilistic modelling, with a particular focus on Gaussian processes, uncertainty quantification, and general machine learning methods, e.g., neural networks, random forests, support vector machines, etc.

Prospective Students

I am eager to supervise Masters and Ph.D. students, particularly those with interests in (Bayesian) optimisation, machine learning and uncertainty quantification, using both traditional statistical methods (i.e., Gaussian processes) and deep learning-based methods. However, I am also open to supervising students with other interests.

Here is a list of current opportunities:

• EPSRC fully-funded studentships (closing 19/02/2024)
• China Scholarship Council and University of Exeter PhD Scholarships (closing 05/01/2024)

Current Students

• (Ph.D.) Ben Carvell: Safety Critical Decision Making under Uncertainty – Machine Learning Approaches for Tactical Air Traffic Control

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Publications

_{Copyright Notice: Any articles made available for download are for personal use only. Any other use requires prior permission of the author and the copyright holder.}

| 2023 | 2022 | 2021 | 2020 | 2019 | 2018 |

2023

• Pepper N, Ath GD, Thomas M, Everson R, Dodwell T. (2023) Context-Aware Generative Models for Prediction of Aircraft Ground Tracks. [PDF]
• Pepper N, Thomas M, De Ath G, Oliver E, Cannon R, Everson R, Dodwell T. (2023) A Probabilistic Model for Aircraft in Climb using Monotonic Functional Gaussian Process Emulators, Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, volume 479, no. 2271, DOI:10.1098/rspa.2022.0607.

2022

• De Ath G, Chugh T, Rahat AAM. (2022) MBORE: Multi-objective Bayesian Optimisation by Density-Ratio Estimation, GECCO 2022 - Proceedings of the 2022 Genetic and Evolutionary Computation Conference, pages 776-785, DOI:10.1145/3512290.3528769.

2021

• De Ath G, Everson R, Fieldsend J. (2021) Asynchronous ε-Greedy Bayesian Optimisation, Uncertainty in Artificial Intelligence 2021, 27th - 30th Jul 2021, Proceedings of the 37th Conference on Uncertainty in Artificial Intelligence, volume 161, pages 578-588. [PDF]
• De Ath G, Everson RM, Fieldsend JE. (2021) How Bayesian should Bayesian optimisation be?, GECCO '21: Genetic and Evolutionary Computation Conference, Proceedings of the Genetic and Evolutionary Computation Conference Companion, DOI:10.1145/3449726.3463164. [PDF]
• De Ath G, Everson RM, Rahat AA-AM, Fieldsend JE. (2021) Greed is Good: Exploration and Exploitation Trade-offs in Bayesian Optimisation, ACM Transactions on Evolutionary Learning and Optimization (TELO), volume 1, no. 1, article no. 1, DOI:10.1145/3425501.

2020

• De Ath G, Fieldsend JE, Everson RM. (2020) What do you Mean? The Role of the Mean Function in Bayesian Optimisation, Genetic and Evolutionary Computation Conference Companion, Cancún, Mexico, 8th - 12th Jul 2020, Genetic and Evolutionary Computation Conference Companion (GECCO ’20 Companion), DOI:10.1145/3377929.3398118.
• De Ath G, Everson RM, Fieldsend J, Rahat A. (2020) ε-shotgun: ε-greedy Batch Bayesian Optimisation, Genetic and Evolutionary Computation Conference (GECCO ’20), Cancún, Mexico, 8th - 12th Jul 2020, Genetic and Evolutionary Computation Conference (GECCO ’20), pages 787-795, DOI:10.1145/3377930.3390154.

2019

• Kristan M, Matas J, Leonardis A, Felsberg M, Pflugfelder R, Kamarainen J-K, Zajc LC, Drbohlav O, Lukezic A, Berg A. (2019) The Seventh Visual Object Tracking VOT2019 Challenge Results, 2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW), 27th - 28th Oct 2019, 2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW), DOI:10.1109/iccvw.2019.00276. [PDF]
• De Ath G. (2019) Object Tracking in Video with Part-Based Tracking by Feature Sampling.
• Kristan M, Leonardis A, Matas J, Felsberg M, Pflugfelder R, Zajc LČ, Vojír̃ T, Bhat G, Lukežič A, Eldesokey A. (2019) The sixth visual object tracking VOT2018 challenge results, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), volume 11129 LNCS, pages 3-53, DOI:10.1007/978-3-030-11009-3_1.

2018

• De Ath G, Everson R. (2018) Visual object tracking: The initialisation problem, Proceedings - 2018 15th Conference on Computer and Robot Vision, CRV 2018, pages 142-149, DOI:10.1109/CRV.2018.00029.

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