School of Computer Science

PGR Seminar with Sharon Pisani

The next PGR seminar is taking place this Friday 21st February at 2PM in JC 1.33a

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

Title: Digital Cultural Landscapes for Sustainable Development in Remote and Island Communities

Abstract: Heritage plays a crucial role in community identity and sustainable development, yet remote and island communities often face challenges in engaging with and protecting their landscapes. This research explores how emergent digital technologies—such as 3D modelling, VR, and AR—can enhance heritage engagement and contribute to sustainable development. Using a practice-led methodology, case studies from Scotland and Malta demonstrate how digital cultural landscapes can support climate action, institutional capacity-building, and sustainable communities. A sustainable virtual museum framework is being developed, linking heritage to real-world environmental and socio-economic challenges. This presentation highlights the findings from these case studies, and the next steps in developing an immersive digital environment for an underwater heritage site.

PGR Seminar with Sachin Yadav and Junyu Zhang

The next PGR seminar is taking place this Friday 14th February at 2PM in JC 1.33a

Below is a title and Abstract for Sachin and Junyu’s talks – Please do come along if you are able.

Sachin Yadav

Title: Reimagining the Digital Gig Economy: Evaluating the economic feasibility and technological capabilities of physical cooperative gig platform

Abstract: The gig economy, fuelled by digital platforms, has transformed the labour markets around the world, offering flexibility but often at the cost of security for the worker and fair compensation. This presentation explores platform cooperatives – a democratically owned and governed alternative – as a potential solution to these challenges. I will delve into the economic feasibility and technological capabilities of physical delivery cooperatives, comparing them to traditional investor-owned platforms. By examining key performance metrics, regulatory environments, and worker empowerment, my ongoing work will assess whether platform cooperatives can achieve a comparable level of service while fostering more equitable working conditions. This presentation aims to spark discussion on the future of the gig economy and the role cooperative models can play in creating a more sustainable digital labour landscape.

Junyu Zhang

Title: Engaging Culture Heritage with Authentic Characters to Support Inclusive Learning

Abstract: Digitalization opens up new opportunities for cultural heritage, and lately the exploration of virtual reality has created new forms of representation of cultural content for educational institutions, museum exhibitions, and heritage preservation organizations. High-fidelity technology allows virtual agents to simulate realistic human appearances and behaviour to interact and engage with their surroundings. This speech presents work-in-progress research regarding designing, creating and utilising authentic characters to strengthen the exhibition of cultural heritage. Through the discussion on research design and practice, this research examines the capability of characters to enrich immersion and communication with heritage. This presentation introduces the realism and authenticity of character design, clarifies the goals for digitalization for inclusive learning opportunities in SDG, and ends with future work.

Seminar, Nobuko Yoshida, Monday 3rd February

Prof. Nobuko Yoshida of Oxford University is visiting us next Monday (3 February).

Nobuko has kindly agreed to give a talk on her work during her visit. The talk will be at 1pm in JC1.33a.

Nobuko Yoshida, University of Oxford, UK
https://www.cs.ox.ac.uk/people/nobuko.yoshida/

Title
Multiparty Session Types: Separation and Encodability Results

Abstract

Multiparty session types (MPST) are a type discipline for enforcing the structured, deadlock-free communication of concurrent and message-passing programs. Traditional MPST have a limited form of choice in which alternative communication possibilities are offered by a single participant and selected by another. Mixed choice multiparty session types (MCMP) extend the choice construct to include both selections and offers in the same choice. This talk first introduces the history and background of types for communications and multiparty session types, relating to the history of Computer Science in Oxford. This talk then presents a mixed choice synchronous multiparty session calculus and its typing system, which guarantees communication safety and deadlock-freedom. We then discuss the expressiveness of nine subcalculi of MCMP-calculus by examining their encodability (there exists a good encoding from one to another) and separation (there exists no good encoding from one calculus to another). The highlight is the binary (2-party) mixed sessions by Casal et al (2022) is strictly less expressive than the MCMP-calculus.

A joint work with Kirstin Peters appeared in LICS’24 (https://arxiv.org/abs/2405.08104)

About the speaker. Nobuko Yoshida is Christopher Strachey Chair of Computer Science in University of Oxford. She is an EPSRC Established Career Fellow and an Honorary Fellow at Glasgow University. Last 10 years, her main research interests are theories and applications of protocols specifications and verifications. She introduced multiparty session types [ POPL’08, JACM ] which received Most Influential POPL Paper Award in 2018 (judged by its influence over the last decade). This work enlarged the community and widened the scope of applications of session types, e.g. runtime monitoring based on Scribble (co-developed with Red Hat) has been deployed to other projects such as cyberinfrastructure in the US Ocean Observatories Initiative (OOI); and widened the scope of her research areas. She received the Test-of-time-award from PPDP’24 and the best paper awards from CC’20, COORDINATION’23 and DisCoTech’23. She received the third Suffrage Science Awards for Mathematics and Computing from MRC for her STEM activity. She is an editor of ACM Transactions on Programming Languages and Systems, ACM Formal Aspects of Computing, Mathematical Structures in Computer Science, Journal of Logical Algebraic Methods in Programming, and the chief editor of The Computer-aided Verification and Concurrency Column for EATCS Bulletin.

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

 

PhD Viva Success: Thomas Hansen

On behalf of the School, we would like to congratulate Thomas Hansen supervised by Dr Edwin Brady who has successfully defended his thesis.

Thanks to Dr Adam Barwell who was internal examiner and Dr Jeremy Yallop from University of Cambridge as external examiner.

Many congratulations to Thomas! 🎉

 

PGR Seminar with Mustafa Abdelwahed and Maria Andrei

The next PGR seminar is taking place this Friday 6th December at 2PM in JC 1.33a

Below is a title and Abstract for Mustafa and Maria’s talks – Please do come along if you are able.

Mustafa Abdelwahed:

Title: Behaviour Planning: A toolbox for diverse planning

Abstract:

Diverse planning approaches are utilised in real-world applications like risk management, automated streamed data analysis, and malware detection. These approaches aim to create diverse plans through a two-phase process. The first phase generates plans, while the second selects a subset of plans based on a diversity model. A diversity model is a function that quantifies the diversity of a given set of plans based on a provided distance function.

Unfortunately, existing diverse planning approaches do not account for those models when generating plans and struggle to explain why any two plans are different.

Existing diverse planning approaches do not account for those models when generating plans, hence struggle to explain why any two plans are different, and are limited to classical planning.

To address such limitations, we introduce Behaviour Planning, a novel toolbox that creates diverse plans based on customisable diversity models and can explain why two plans are different concerning such models.

Maria Andrei: 

Title: Leveraging Immersive Technology to Enhance Climate Communication, Education & Action

Abstract: Climate change represents one of the most pressing challenges of our time, not only in its environmental impacts, but also as a pivotal science communication problem. Despite widespread scientific consensus on the causes and mitigation strategies for climate change, public understanding remains deeply fragmented and polarized. This disconnect hinders the collective action required from individuals, organizations, and policymakers to combat global warming effectively. My research explores the potential of immersive technologies to bridge the gap between scientific knowledge and public understanding by leveraging experiential learning experiences to inspire the attitudinal and behavioural shifts necessary to address climate change.

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.