Research Groups

Doors Open @ Computer Science, St Andrews on Thursday 1 May 2025, 10am-4pm (drop in)

We are holding a Doors Open event on Thursday, 1 May 202,5 and would love for you and your colleagues to visit us at this event.  

Our school is growing, and we want to make sure we are listening to organisations locally, nationally, and internationally. Our hope is that the day is a chance to share and discuss some of the exciting projects going on by our staff and students. We’d love to hear about what you are doing and see if there are any interesting ways to work together.  

We have created an events webpage with details and outlines of the projects which will be on show; we are adding more every day (Doors Open @ CS). We will also have our Hot Tattie sessions upstairs in 1.33b at various times during the day. 

So we can plan refreshments, it would be great if you could register: Doors Open @ Computer Science 2025  

If you have any questions, please get in touch. 

We are hiring a Professor in Artificial Intelligence

The University of St Andrews wishes to make an appointment to the Johann and Gaynor Rupert Chair in Artificial Intelligence in the School of Computer Science.

You will be an outstanding scholar of international standing in Artificial Intelligence with a proven track record of securing significant grant funding and leading high-quality externally funded research projects. The successful candidate will be expected to have a range of interests, be able to work across disciplines, and strengthen and complement existing work within the School to make an outstanding contribution to the field’s advancement through research outputs.

See full advert here: Professor in Artificial Intelligence (Chair) – AC2605LS

SACHI Seminar, Stavroula Pipyrou – Radical Imagination: Knowledge Through Generations

We are pleased to share our upcoming SACHI seminar this week by Dr Stavroula Pipyrou, a Senior Lecturer in Social Anthropology at the University of St Andrews and Founding Director of the Centre for Minorities Research.

📅 Wednesday 2nd April  | 🕛 13:00 – 14:00 PM | 📍 JCB, Room 1.33A

Title:

Radical Imagination: Knowledge Through Generations

Abstract:

“Today we will engage with insights from a young Greek interlocutor who did not live the Cold War period firsthand. She relates to the legacies of the Cold War through radical imagination, projecting that it is only logical that the affects of the era have left irreversible psychological marks on the people who experienced it. The talk proposes a theory of psychic time and generational battles for belonging. There is a critique of history as taught in school textbooks when compared to the lived experiences of history in the present.”

Bio:

Stavroula is Senior Lecturer in Social Anthropology at the University of St Andrews, Founding Director of the interdisciplinary Centre for Minorities Research and editor of the interdisciplinary book series Routledge Advances in Minority Studies. She works on minority politics, displacement, governance, and the Cold War. She is the author of “The Grecanici of Southern Italy: Governance, Violence, and Minority Politics” (University of Pennsylvania Press, 2016) and “Lurking Cold War: Life Through Historical Communion” (Berghahn 2025). Lurking Cold War explores the entangled registers of the Cold War that continue to stalk the social landscape in Italy and Greece. Critiquing the connections between global categories and individual experiences, Lurking foregrounds Cold War resonances through materiality, imagination, speculation and affect, in literature, bureaucracy and in the family. A theory of methexi illustrates how people and history are brought into communion, blurring the boundaries between known and unknown, reality and imagination, and form and interpretation. The result is an articulation of history that matters in a way that matters.

SACHI Seminar, Mark Zarb – Bridging Minds and Machines: Redefining Computing Education

We are pleased to share our upcoming SACHI seminar by Dr Mark Zarb, an Associate Professor based within the School of Computing, Engineering and Technology at RGU:

📅 26th March | 🕛 13:00 – 14:00 PM | 📍 JCB, Room 1.33A

Title:

Bridging Minds and Machines: Redefining Computing Education

Abstract:

Since 2009, Dr Zarb has been exploring the evolving landscape of pedagogical research, collecting ideas from across disciplines and trends. In this acronym-filled talk, he offers a guided tour through some of the latest research at RGU — from grappling with the ethical dilemmas posed by conversational AI in education, to exploring “shadow podcasts” as informal learning tools. We will look at practical challenges, unexpected questions and at how rapidly shifting technology continues to shape how (and why) we teach and learn.

Bio

Dr Mark Zarb is an Associate Professor based within the School of Computing, Engineering and Technology at RGU

His main research focus is within computing education, having led international working groups on transitions into higher education in 2018 and post-pandemic educational landscapes in 2021 and 2022.

He received his PhD (2014, University of Dundee) for work exploring the role of verbal communication styles in pair programming. His various roles and experiences allow him a wide and international perspective on computing education.

SACHI Seminar with Aluna Everitt – Democratising the Design and Development of Emerging Technologies

We are pleased to share our upcoming SACHI research seminar by Dr Aluna Everitt, a lecturer in the Department of Computer Science and Software Engineering at the University of Canterbury, New Zealand:

📅 Today | 🕛 12:00 – 1:00 PM | 📍 JCB, Room 1.33B

Title:

Democratising the Design and Development of Emerging Technologies

Abstract:

My research focuses on democratising the development of emerging technologies. More specifically, by establishing accessible approaches for designing and building emerging technologies such as robotics, wearables, and shape-changing interfaces. To advance the field, my research focuses not only on understanding these technologies (e.g., their design), but also how to build them (e.g., engineer them), and how to innovate with them (e.g., application). In this talk, I will go into detail about some of the projects I have worked on around this topic across the fields of HCI, Design, and Engineering.

Bio:

Dr. Aluna Everitt is a lecturer in the Department of Computer Science and Software Engineering at the University of Canterbury, New Zealand. Prior to moving to Christchurch (NZ), she was a Research Associate in the Cyber-Physical Systems group at the University of Oxford and a Junior Research Fellow at Kellogg College, University of Oxford. She was also a Senior Visiting Researcher and postdoc at the University of Bristol (BIG Lab). Dr. Everitt was awarded her PhD in Computer Science from Lancaster University, specializing in Human-Computer Interaction (HCI). As a multi-disciplinary researcher, her areas of interest and expertise lie across the fields of HCI, Design, and Engineering. She has a particular interest in conducting both quantitative and qualitative research which combines a mix of engineering fabrication approaches for iterative prototyping, together with collaborative design (co-design) to encourage users and experts from different domains to develop content and applications for the next generation of interactive hardware systems and interfaces (e.g., shape-changing displays, wearables, and robotics).

Fully funded PhD scholarship in Multi-agent Path Planning

Lead supervisor: Professor Ian Miguel

Application deadline: 1 March 2025

Project description:

Planning is a fundamental discipline of Artificial Intelligence, which asks us to find a sequence of actions transforming an initial state into a goal state. This project focuses on multi-agent path planning (also known as multi-agent path finding), where a set of mobile agents is navigated from starting positions to target positions. MAPP is the focus of intense research effort because it has many challenging real-world applications in robotics, navigation, the video game industry, and automatic warehousing. Automatic warehousing is one of the most challenging domains and the focus of the greatest investment. For example, Amazon have invested heavily in robot-equipped warehouses. It is performed on a huge scale (thousands of robots in warehouses containing many thousands of shelves and products) with the need to find an efficient solution quickly so that the robots are always safely moving towards their goals. The typical layout of a warehouse increases difficulty further: shelves are packed tightly into the space, reducing the capacity for movement of the robots.

MAPP is inherently very difficult — there is no known “cheap” method to produce high quality solutions quickly at the scale required. Current approaches fall into two categories, both relying on AI techniques that search through the vast space of possible solutions. Those that guarantee optimality struggle to scale, while approaches that scale do so at the cost of reduced solution quality. This proposal is to advance the state of the art in optimal MAPP significantly through a novel combination of path planning and constraint programming. Constraint programming is a powerful automated reasoning technique that allows us to model a complex decision-making problem such as MAPP by describing the set of choices that must be made (e.g. which path a robot should take) and the set of constraints that specify allowed combinations of choices (e.g. robots cannot collide). This model is presented to a constraint solver, which searches for solutions automatically, using powerful deduction mechanisms to reduce search considerably.

The project includes the following objectives:

A New Modelling Perspective: The model input to a constraint solver is crucial to the efficiency with which solutions can be found. Our proposed innovation is in how MAPP is modelled. We will exploit the many equivalencies in these problems, for example equivalent routes between locations, and equivalent resources in terms of the robots. While these remain in the model they must potentially all be explored, wasting enormous effort. Instead of modelling the warehouse layout at a fine level of detail, the current default leading to the consideration of a vast number of equivalent paths, we will abstract the fine-grained grid representation into larger regions, for example representing an entire corridor between two shelves.

Ensuring Validity: The research challenge in adopting this more abstract modelling perspective is to ensure that plans found with this reduced representation are valid in the real warehouse by, for example, constraining these regions so that their capacities are respected and the flow of traffic within them is such that collisions and deadlocks cannot occur.

Evaluation and refinement: We will evaluate our new model on benchmark problems drawn from the competitions where state of the art MAPP solvers compete. This will allow us to gauge progress and refine and improve our new approach.

The result of this research will be to improve the scalability of optimal solvers, producing better quality solutions, increasing the throughput of a warehouse, and reducing operational costs.

Eligibility Criteria

We are looking for highly motivated research students willing to be part of a diverse and supportive research community. Applicants must hold a good Bachelor’s or Master’s degree in Computer Science, or a related area appropriate for their proposed topic of study.

International applications are welcome. We especially encourage female applicants and underrepresented minorities to apply. The School of Computer Science was awarded the Athena SWAN Silver award for its sustained progression in advancing equality and representation, and we welcome applications from those suitably qualified from all genders, all races, ethnicities and nationalities, LGBT+, all or no religion, all social class backgrounds, and all family structures to apply for our postgraduate research programmes.

Value of Award
  • Tuition scholarships cover PhD fees irrespective of country of origin.
  • Stipends are valued at £19,795 per annum (or the standard UKRI stipend, if it is higher).
To apply:

Interested applicants can contact Professor Ian Miguel with an outline proposal.

Full instructions for the formal application process can be found at How to apply – School of Computer Science – University of St Andrews

 

PGR Seminar with Zhongliang Guo

The next PGR seminar is taking place this Friday at 2PM in JC 1.33a

Below is a title and Abstract for Zhongliang’s talk– Please do come along if you are able.

Title: Adversarial Attack as a Defense: Preventing Unauthorized AI Generation in Computer Vision

Abstract: Adversarial attack is a technique that generate adversarial examples by adding imperceptible perturbations to clean images. These adversarial perturbations, though invisible to human eyes, can cause neural networks to produce incorrect outputs, making adversarial examples a significant security concern in deep learning. While previous research has primarily focused on designing powerful attacks to expose neural network vulnerabilities or using them as baselines for robustness evaluation, our work takes a novel perspective by leveraging adversarial examples to counter malicious uses of machine learning. In this seminar, I will present two of our recent works in this direction. First, I will introduce the Locally Adaptive Adversarial Color Attack (LAACA), which enables artists to protect their artwork from unauthorized neural style transfer by embedding imperceptible perturbations that significantly degrade the quality of style transfer results. Second, I will discuss our Posterior Collapse Attack (PCA), a grey-box attack method that disrupts unauthorized image editing based on Stable Diffusion by exploiting the common VAE structure in latent diffusion models. Our research demonstrates how adversarial examples, traditionally viewed as a security threat, can be repurposed as a proactive defense mechanism against the misuse of generative AI, contributing to the responsible development and deployment of these powerful technologies.

AI Seminar Tuesday 19th November – Francesco Leofante

The School is hosting an AI seminar on Tuesday 19th November at 11am in JCB1.33A/B

Our speaker is Francesco Leofante from Imperial College London.

Title:

Robustness issues in algorithmic recourse.

Abstract:

Counterfactual explanations (CEs) are advocated as being ideally suited to providing algorithmic recourse for subjects affected by the predictions of machine learning models. While CEs can be beneficial to affected individuals, recent work has exposed severe issues related to the robustness of state-of-the-art methods for obtaining CEs. Since a lack of robustness may compromise the validity of CEs, techniques to mitigate this risk are in order. In this talk we will begin by introducing the problem of (lack of) robustness, discuss its implications and present some recent solutions we developed to compute CEs with robustness guarantees.

Bio:

Francesco is an Imperial College Research Fellow affiliated with the Centre for Explainable Artificial Intelligence at Imperial College London. His research focuses on safe and explainable AI, with special emphasis on counterfactual explanations and their robustness. Since 2022, he leads the project “ConTrust: Robust Contrastive Explanations for Deep Neural Networks”, a four-year effort devoted to the formal study of robustness issues arising in XAI. More details about Francesco and his research can be found at https://fraleo.github.io/.

Fully funded PhD scholarship in software ethics

Supporting ethical deliberation in the software lifecycle

 

Lead supervisor: Dr Dharini Balasubramaniam

Application deadline: 1 March 2025

Project description:

Software ethics covers a broad spectrum of concerns including accountability, fairness, privacy and data protection, transparency, safety, security, accessibility, digital inclusion and sustainability. Much of the current dialogue on software ethics relates to the development, deployment and use of AI-based solutions, although there are ethical concerns related to most, if not all, software application domains. The pervasive nature of software, its critical importance to the functioning of many sectors, and the opaque nature of software-supported decision making in some domains all make it vital that ethical issues are explicitly considered throughout the software lifecycle.

There is generic ethics guidance, such as the ACM / IEEE Software Engineering Code of Ethics and sets of ethical principles specifically aimed at domains such as AI, available to software engineers. Generic and specific concepts such as value-based software development and responsible AI have been proposed to encourage ethical software development. However, there is still a lack of processes, notations, tools and training available to software professionals to support systematic ethical deliberation and ethics-driven development in practice.
This project will explore and attempt to address this gap. The student will design and develop ways to explicitly capture ethical requirements, risks and mitigations as first-class concepts in software artefacts. They will implement tools that work with these specifications to analyse the compliance of software artefacts with ethical requirements, and highlight potential violations and consequences. Interviews with software professionals and service providers may be used to inform and evaluate the efficacy and viability of outcomes. Open-source projects in chosen application domains may also be used for case study-based evaluation.

Topics of interest:

Specific topics of interest include, but are not limited to:

  • A framework of ethical concerns that apply to software,
  • Notations to represent ethical requirements, risks and mitigations as first-class concepts in software design and implementation,
  • Tool support for the representation and analysis of ethical concerns in software artefacts,
  • Process and tool support for considering specific aspects of software ethics, such as bias avoidance, transparency, sustainability or accessibility, and
  • Integration of ethical training and deliberation within project and product management environments.

The scholarship:

We have one fully-funded scholarship available, starting in September 2025. The scholarship covers all tuition fees irrespective of country of origin and includes a stipend valued at £19,705 per annum. More details of the scholarship can be found here: https://blogs.cs.st-andrews.ac.uk/csblog/2024/10/24/phd-studentships-available-for-2025-entry/, but please note the different application deadline.

Eligibility criteria:

We are looking for highly motivated research students keen to be part of a diverse and supportive research community. Applicants must hold a good Bachelor’s or Master’s degree in Computer Science, or a related area appropriate for the topic of this PhD.

International applications are welcome. We especially encourage female applicants and underrepresented minorities to apply. The School of Computer Science was awarded the Athena SWAN Silver award for its sustained progression in advancing equality and representation, and we welcome applications from those suitably qualified from all genders, all races, ethnicities and nationalities, LGBT+, all or no religion, all social class backgrounds, and all family structures to apply for our postgraduate research programmes.

To apply:

Interested applicants can contact Dharini Balasubramaniam with an outline proposal. Full instructions for the formal application process can be found at https://www.st-andrews.ac.uk/computer-science/prospective/pgr/how-to-apply/.

The deadline for applications is 1 March 2025.

Fully funded PhD Scholarship in Hardware Simulation at Scale

 

As the Internet ofThings (IoT) expands, the number of connected devices is expected to reach close to 30 billion by 2030. These devices range from simple sensors to complex embedded systems, each with unique characteristics and communication protocols. Simulating such a vast and diverse array of devices presents a significant challenge in terms of scalability, accuracy, and efficiency. This PhD project aims to develop a comprehensive framework for simulating many (1000s, 10,000s, 1,000,000s) heterogeneous IoT devices, at (hopefully) close to real-time speeds. The project will focus on designing a specialised languages for describing hardware and simulations, creating an efficient simulation environment, and exploring hardware acceleration techniques to achieve high performance and scalability.

Previous research in this area has primarily focused on simulating individual devices, smaller networks, or using simplified models that do not fully capture the intricacies of real-world IoT systems. This project seeks to address these limitations by developing a scalable simulation framework that can accurately model the behaviour of billions of heterogeneous devices, advancing the state-of-the-art in simulation languages, distributed computing, and hardware acceleration.

The project will be structured around three core research ideas:

  • Simulation Languages for Heterogeneous Embedded Devices: The first research objective is to explore the creation of a specialised language for describing the behaviour and interactions of heterogeneous IoT devices. This language will need to be expressive enough to capture the wide range of device architectures and communication protocols found in IoT systems. The language will also support modularity and extensibility, allowing users to easily incorporate new device types and behaviours into the simulation.
  • Development of a Scalable Simulation Environment: The second research objective is to create a simulation environment that can efficiently emulate IoT devices at scale, across multiple simulation servers. This environment will be designed to support distributed computing, allowing for parallel execution of simulated devices across a large number of servers. The project will explore various techniques for load balancing, synchronisation, and communication between servers to ensure that the simulation remains efficient and accurate as the scale increases.
  • Hardware Acceleration for Large-Scale Simulations: The third research objective is to investigate the use of hardware acceleration techniques, such as Field Programmable Gate Arrays (FPGAs) and Graphics Processing Units (GPUs), to improve the performance of large-scale IoT simulations. This aspect of the project will focus on identifying the components of the simulation that can be offloaded to specialised hardware, and developing algorithms and architectures that leverage this hardware to achieve significant performance gains.

Topics of Interest

  • Heterogeneous Systems Modelling: Techniques for accurately modelling the diverse architectures and communication protocols of IoT devices.
  • Distributed Simulation: Methods for efficiently distributing simulations across multiple servers, including load balancing, synchronisation, and inter-server communication.
  • Simulation Languages: Design and implementation of specialised languages for describing complex IoT devices and networks.
  • Hardware Acceleration: Exploration of FPGA, GPU, and other hardware acceleration technologies to enhance the performance of large-scale simulations.
  • Scalability and Performance Optimisation: Strategies for ensuring that the simulation framework can handle the increasing complexity and scale of IoT networks.
  • Validation and Verification: Techniques for validating and verifying the accuracy and reliability of large-scale IoT simulations.

The Scholarship

We have one fully-funded scholarship available, starting in September 2025, which will be awarded to competitively to the best applicant. The scholarship covers all tuition fees (irrespective of country of origin) and comes with a stipend valued at £19,705 per annum. More details can be found here: https://blogs.cs.st-andrews.ac.uk/csblog/2024/10/24/phd-studentships-available-for-2025-entry/

International applications are welcome. We especially encourage female applicants and underrepresented minorities to apply. The School of Computer Science was awarded the Athena SWAN Silver award for its sustained progression in advancing equality and representation, and we welcome applications from those suitably qualified from all genders, all races, ethnicities and nationalities, LGBT+, all or no religion, all social class backgrounds, and all family structures to apply for our postgraduate research programmes.

To Apply

Informal enquiries can be directed to Tom Spink. Full instructions for formal applications can be found at https://www.st-andrews.ac.uk/computer-science/prospective/pgr/how-to-apply/

The deadline for applications is 1 March 2025.