Research projects

Here is a list of some of the funded research projects that I am involved in. Some of these projects have positions available for PhD students and Postdoctoral Research Associates. I am always interested in recruiting excellent PhD students and Postdoctoral Research Associates through externally funded fellowship schemes and I am always happy to discuss the possibility of developing bespoke projects with potential students and fellows. If you are interested in reading for a PhD under my supervision, or working with me as research associate, please Get in touch.

Multiscale multiphysics structured interfaces

Whilst research in metamaterials (structured materials that can control waves and energy) has undergone a renaissance, the majority of work has focused on controlling a single physical domain - usually light. In contrast, this project seeks to develop a mathematical framework to study, design, and create multiphysical metasurfaces (Maradudin, 2011) capable of manipulating waves across many physical phenomena. Metasurfaces are structured interfaces where two or more physical systems interact, such as solids and fluids. Structured interfaces arise in many real-world applications - anywhere two media meet, from antenna designs, to the interface between the ocean and sea-bed, the foundations of modern buildings, medical implants, and safety-critical power generation components.

Research team

Student: Mr Jack Wildman
Primary supervisor: Prof Daniel Colquitt
Secondary supervisor: Dr Stewart Haslinger
Post-doctoral Research Associate: Dr Katie Madine

This work is graciously funded by The Leverhulme Trust through Research Project Grant RPG-2022-261 and is undertaken in collaboration with KANDE International Ltd

Machine Learning for Data Driven Sound Propagation Modelling

This project will develop a series of high-fidelity digital twins capable of encapsulating a number of critical dynamic phenomena, which affect the propagation of sound waves through ocean environments, including internal waves, multi-scale structural thermal and temporal variations and fluctuations, scattering by non-smooth interfaces and boundaries (e.g. semi-submerged structures, sea bed, surface), currents, eddies, and fronts. The resulting sound propagation models, and advanced understanding embodied within these models, will enable the Royal Navy and other users of the ocean, the means to improve the effectiveness of their sonar systems and achieve the best results from sonar deployments and operations.

The developed models will be capable of intelligently adapting their approach and selecting the best solution method based on the input data, computational and operational constraints, desired outputs, and physical configuration. These models will incorporate advances in Finite Element Methods, via GPU parallel computing capability that has been largely untapped for underwater acoustics, along with hybrid semi-analytic coupling methods. Stochastic analysis of physical scattering models, incorporating real-world data, will provide a major step forward in the capability available to investigate dynamic ocean mechanisms. Analysis of simulated and measured oceanographic and acoustic data, including the use of artificial intelligence and machine learning techniques, will be supported by a parallel PhD project in the Department of Mathematical Sciences on Advances in mathematical modelling to study complex sound propagation in an inhomogeneous moving ocean. This will help to identify the properties and behaviour of different mechanisms. New ways of representing the specified mechanisms will be developed, and environment-specific modelling tools and innovative mathematical representations will be implemented.

Research team

Student: Mr Finley Boulton
Primary supervisor: Prof Daniel Colquitt
Secondary supervisor: Dr Sebastian Timme
Industrial Supervisor: Dr Duncan Williams, Dstl

The project, undertaken in collaboration with the Dstl, is hosted at the University of Liverpool and is part of the Distributed Algorithms CDT and Signal Processing research community - a large, social and creative research group that works together solving tough research problems. The project started on October 1st 2023 and runs for four years.

MUSICA: Modelling UltraSonic Inspection of Challenging defects for Automated analysis

We will develop automated ultrasonic data analysis tools to improve the reliability of detection, sizing, and characterisation of defects which occur in high safety significance industrial plant. The project will develop capability for defects of critical industrial importance, targeting two species: Thermal Fatigue (a service induced species) and Hydrogen cracking (a manufacturing/welding defect). Both species are known to occur and often materially impact plant availability/longevity. This project will also enable capability for other challenging defect species going forward, such as stress corrosion cracks.

Research team

This project is in collaboration with Dr. Stewart Haslinger (PI), Prof Daniel Colquitt, Dr. W. Christian, Prof. Jason Ralph, Dr Thomas Beckingham, Prof Mike Lowe, Dr Peter Huthwaite, & Dr Georgios Sarris.

This work is funded by The Research Centre for Non-Destructive Evaluation as a vision-focused core project.

Using machine learning and artificial intelligence to improve the tracking of vessels in sonar spectrograms

This PhD project explores creating an AI model that can correctly classify quiet targets in waterfall (sonar) data. Currently, waterfall data is analysed by human operators; however, this is time-consuming and expensive; these human operators outperform traditional automated passive contact follower algorithms, such as the Kalman and Alpha-Beta filters: these filters are susceptible to the abundant underwater noise and struggle with crossing tracks and quiet contacts. In contrast, humans can use their experience to learn how to mitigate the challenging aspects of the task. An automatic detection and tracking model that is more accurate and robust than traditional methods would reduce the human operator’s workload.

Research team

Student: Mr William Shaw
Primary supervisor: Dr Murat Uney
Secondary supervisor: Prof Daniel Colquitt
Industrial Supervisor: Dr Cerys Jones, Ultra

The project, undertaken in collaboration with the Ultra Group, is hosted at the University of Liverpool and is part of the Distributed Algorithms CDT and Signal Processing research community - a large, social and creative research group that works together solving tough research problems. The project started on October 1st 2022 and runs for four years.

Underwater acoustics: Advances in mathematical modelling to study complex sound propagation in an inhomogeneous moving ocean

The aim of this well-funded PhD project is to develop models for underwater sound propagation through a moving inhomogeneous ocean, with an emphasis on enhancing the understanding of critical dynamic aspects, including:

  • Internal waves;
  • Microstructure variability
  • Scattering by rough surfaces, both stationary (seabed) and moving (sea surface); high sea states bring additional dynamic challenges such as large waves and infusion of air bubbles;
  • Seasonal, diurnal, and inter-diurnal changes;
  • Slow-moving horizontal currents, fronts, and eddies.

There is a lack of clarity within current literature as to the optimal representation of these dynamic phenomena within models, even for simplified two-dimensional cases. This project will address that issue by providing new insights that will also facilitate the development of three-dimensional and full four-dimensional, time-dependent propagation models.

Research team

Student: Miss Yiyi Whitchelo
Primary supervisor: Dr Stewart Haslinger
Secondary supervisor: Prof Daniel Colquitt
Industrial Supervisor: Dr Duncan Williams, Dstl

A 4-year fully-funded EPSRC i-CASE studentship with the Defence Science and Technology Laboratory (Dstl) covering UK tuition fees, maintenance above the average UKRI Doctoral Stipend rate and an allowance for training, conference and research expenses.

Task 64: Modelling and Algorithm Development

Development of a modelling capability to simulate acoustic signal propagation through an oceanic environment, interactions of the signals with objects within the environment, and to predict the signals received by sensors.

Research team

This project is in collaboration with Prof Jason Ralph (PI), Prof Daniel Colquitt, Prof Simon Maskell, & Dr Thomas Beckingham.

We are supporting Sonardyne's work on Task 64 under the Defence Science and Technology Laboratory's Progeny Procurement Framework.

Recently completed projects

Here is a list of some of the funded research projects that I have recently been involved in. If you are interested in the outputs or discussing potential follow-on projects or applications, please do get in touch.

Task 79: Mathematics of Sensing

As part of the Dstl Future Sensing Programme, this Foundry project aimed to identify, understand, and assess novel mathematical approaches to a variety of problems in the Intelligence, Surveillance and Reconnaissance (ISR) domain.

Research team

Prof Jason Ralph (UoL, EEE), Prof Daniel Colquitt (UoL), Dr Stewart Haslinger (UoL, Maths), Dr Azaria Coupe (QinetiQ), Dr Mark Everitt (Loughborough, Physics), Prof Tristan Pryer (Bath, Maths), Prof Alexander Cox (Bath, Maths), Dr Luca Zanetti (Bath, Maths), Dr Christopher Rowlatt (Bath, Maths), Dr Silvia Gazzola (Bath, Maths).