About the Project

Modern society increasingly relies on responsible and explainable AI automation, intelligent systems, and multi-source data to support AI–human collaborative decision-making in complex socio-technical environments. This research theme addresses major technical, environmental, societal, and ethical challenges through interdisciplinary approaches spanning engineering, computer science, telecommunications, neuroscience, political economy, finance, creative media, and sports. It aligns closely with the expertise of Loughborough University’s Institute for Digital Technologies, which focuses on advanced digital infrastructures, trustworthy AI, intelligent networks, and immersive technologies to drive meaningful societal impact. To align more closely with our priorities, applicants are expected to focus on at least one of the following realms:

1. Transformative Potential of AI - Artificial intelligence and big data analytics offer transformative opportunities to address some of the world’s most pressing challenges. These include the development of sustainable infrastructure, improvements in energy efficiency, reductions in carbon footprints, responsible management of scarce resources, intelligent transportation systems, resilient communication networks, and advanced digital healthcare. Central to this theme is the creation of responsible, transparent, and human-centred AI that benefits society while ensuring fairness, accountability, and inclusivity.
2. Foundational Technologies for Decision-Making - Key underlying technologies include responsible AI methodologies, machine learning, neuromorphic computing, optimisation techniques, game theory, and Bayesian inference. These approaches facilitate decision-making under uncertainty and enable robust forecasting.
3. Intelligent Innovations in Diverse Applications for Impact - In engineering, we focus on how AI drives applications in intelligent transportation, reconfigurable and adaptive telecommunication networks, and integrated IoT and sensor networks for digital twins and predictive maintenance.

In computer science, we welcome research spanning human–computer interaction, haptic systems, immersive metaverse technologies, natural language processing using large language models, and machine-learning-based systems for detecting fraud, cyber threats, and disinformation to enhance usability, security, and social justice.

In finance and political economy, we are interested in the regulation and governance of AI by states and international organisations, as well as the impact of AI on forecasting models, algorithmic trading, risk assessment tools, and economic simulations that incorporate behavioural and market dynamics.

In creative media and sports, we are interested in how AI enables and supports performance analytics via athlete monitoring, digital content creation, personalised audience engagement, and optimisation of training strategies.

Our Strength: Interdisciplinary Integration

At the core of this research theme is the development and analysis of advanced AI and machine-learning techniques, including deep learning, reinforcement learning, federated learning, adversarial learning, generative AI, and large language models. By integrating engineering, computer science, and the social sciences, this theme provides a flexible and interdisciplinary foundation for impactful research. It offers PhD students a unique opportunity to innovate within a collaborative, cross-disciplinary environment and to contribute to AI solutions that promote sustainable, inclusive, and equitable societies.

Supervisor

Dr Xiyu Shi (X.Shi@lboro.ac.uk)

Tuition fees for 2026-27 entry

• UK fee - £5,238 Full-time degree per annum
• International fee - £29,500 Full-time degree per annum

Fees for the 2026-27 academic year apply to projects starting in October 2026, February 2027 and July 2027.

UK tuition fees for 2026/27 are currently to be confirmed pending the release of the UKRI recommended rates. Once published, these rates will be subject to formal approval by the University before being confirmed.

Opportunity Details

• Target Start Date: October 2026
• Full time or part time available.
• Open to UK and international applicants.

How to Apply

We welcome discussions with interested candidates.

• Step 1: Interested applicants should first contact Xiyu Shi (X.Shi@lboro.ac.uk) to discuss your research interests and funding options.
• Step 2: Applicants are then strongly encouraged to contact potential supervisors with a CV, academic transcripts, and confirmation of funding sources or planned funding sources.
• Step 3: following any informal discussion, applicants are invited to make a formal application on the Loughborough Website.