海角社区

Doctoral Researcher: Saeed Hajisafari
Start date: April 2026
Supervisors: Dr Alister Smith and Professor Craig Hancock
Schools: Civil Engineering (ABCE)

This PhD is co-funded and co-supervised by Network Rail.

Saeed's aim is to enhance the utility of InSAR (Interferometric Synthetic Aperture Radar) in railway earthworks asset management.

He will deliver improved InSAR techniques - including an advanced SBAS methodology and AI-driven spatial resolution upgrades - for more accurate monitoring of railway earthworks.

Additionally, he will integrate environmental data through data fusion and develop automated machine learning tools for anomaly detection and risk assessment. The effectiveness of the developed approach will be validated and refined through comparisons with alternative observations and measurements.

Doctoral Researcher: Ameer Hamza
Start date: April 2026
Supervisors: Dr Alister Smith, Dr Matthew Frost and Dr Haitao Lan
Schools: Civil Engineering (ABCE)

This PhD is co-funded and co-supervised by Network Rail.

Ameer's aims are to enhance understanding of how drainage systems impact slope hydromechanical behaviour and then develop an improved design and maintenance framework for long-term performance and climate resilience.

He will assess the influence of various slope drainage systems on pore pressures, groundwater movement, shear key effects and hydrological interception.

In addition, he will explore innovative materials to enhance drainage system performance, evaluate historical asset records, and integrate physical and numerical modelling.

Doctoral Researcher: Arezoo Ariyaei
Start date: April 2026
Supervisors: Dr Ashraf El-Hamalawi, Dr Asma Adnane, and Dr Alister Smith
Schools: Civil Engineering (ABCE) and Computer Science

Arezoo aims to develop capabilities to forecast deterioration and failure in earthworks driven by weather cycles and climate change scenarios. This will enable a transition from responsive maintenance interventions / renewals to predictive, proactive and targeted approaches that help to avoid failures.

By integrating numerical simulations, probabilistic techniques and AI analytics, earthwork prognoses could be expressed in the form of time-to-failure and / or probability of survival under extreme weather events.

Start date: July 2026
Supervisors: Professor Craig Hancock, Dr Hui Fang and Dr Alister Smith
Schools: Civil Engineering (ABCE) and Computer Science

Current earthworks assessment remains largely based on visual inspection of the surface. Subsurface deterioration is often missed, and failures occur without warning.

This PhD project aims to develop novel diagnostic techniques for earthwork asset condition appraisal and deterioration detection, helping us to answer the question: How close to failure is the asset?

By integrating a suite of state-of-the-art sensors and monitoring technologies with data fusion and AI analytics, the research will enable timely identification of deterioration processes and assessment of their evolution/extent.

Start date: October 2026
Supervisors: Dr Haitao Lan, Dr Ana Blanco and Dr Alister Smith
Schools: Civil Engineering (ABCE)

This PhD project will investigate the impact of different intervention types - including structural measures, modified materials, vegetation, drainage and covers or barriers - on the hydromechanical behaviour and properties of earthworks, focusing on their vulnerability to climate and weather extremes such as floods, droughts and cyclical wet-dry conditions.

It will explore whether novel interventions can be developed to reduce vulnerability and enhance recovery from these extremes, evaluating which interventions provide the most significant improvements to resilience.

In addition, the research will assess intervention carbon- and cost-effectiveness and develop strategies to optimise the type and timing of their deployment.

Start date: October 2026
Supervisors: Dr Mark Jepson, Dr Matthew Frost and Dr Alister Smith
Schools: Civil Engineering (ABCE) and Materials (AACME)

This PhD project aims to advance understanding of how environmental (weather) cycles drive deterioration in geomaterials.

It will focus on the soil micro-structure evolution and how this links to macro-scale behaviour, using advanced laboratory tests, imaging techniques and computer simulations.

The outcomes will support the development of strategies to mitigate these deterioration processes and improve the resilience of geotechnical infrastructure.

Start date: October 2026
Supervisors: Dr Ana Blanco, Dr Matthew Frost and Dr Alister Smith
Schools: Civil Engineering (ABCE)

This PhD will develop computer vision techniques to enhance visual inspection of railway earthworks.

The researcher will use imagery from asset inspections and drones to automatically detect defects such as cracking, erosion and drainage problems. They will integrate these with LiDAR and track geometry data to provide objective indicators of condition and deterioration.

The project will deliver automated inspection tools that improve consistency, enable earlier detection of instability, and enhance the safety and resilience of railway infrastructure.