PhD

PGR Seminar with Carla Davesa Sureda

The next PGR seminar is taking place this Friday 22nd November at 2PM in JC 1.33a

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

Title:

Towards High-Level Modelling in Automated Planning

Abstract:

Planning is a fundamental activity, arising frequently in many contexts, from daily tasks to industrial processes. The planning task consists of selecting a sequence of actions to achieve a specified goal from specified initial conditions. The Planning Domain Definition Language (PDDL) is the leading language used in the field of automated planning to model planning problems. Previous work has highlighted the limitations of PDDL, particularly in terms of its expressivity. Our interest lies in facilitating the handling of complex problems and enhancing the overall capability of automated planning systems. Unified-Planning is a Python library offering high-level API to specify planning problems and to invoke automated planners. In this paper, we present an extension of the UP library aimed at enhancing its expressivity for high-level problem modelling. In particular, we have added an array type, an expression to count booleans, and the allowance for integer parameters in actions. We show how these facilities enable natural high-level models of three classical planning problems.

Doughnuts will be available! 🍩

Fully funded PhD scholarship in Algorithms for Data Science

Lead supervisor: Dr Peter Macgregor

Application deadline: 1 March 2025

Project description:

Modern data science and machine learning applications involve datasets with millions of data points and hundreds of dimensions. For example, deep learning pipelines produce massive vector datasets representing text, image, audio and other data types. The analysis of such datasets with classical algorithms often requires significant time and/or computational resources which may not be available in many applications.

This motivates the development of a new generation of fast algorithms for data analysis, running in linear or sub-linear time and often producing an approximate result rather than an exact one. Moreover, the dataset may change over time, requiring dynamic algorithms which handle updates efficiently.

This project will tackle aspects of the design, analysis, and implementation of algorithms for processing large dynamic datasets, with the aim to develop new algorithms with state-of-the-art practical performance and/or theoretical guarantees. This could involve performing new analysis of existing algorithms, designing new algorithms with provable guarantees, or implementing heuristic algorithms with state-of-the-art empirical performance.

Possible Directions

Potential areas of research, depending on the interests of the candidate include:

  • Developing improved nearest-neighbour search algorithms (e.g., based on kd-trees, HNSW, locality-sensitive hashing).
  • Exploring any connection between hierarchical clustering algorithms and nearest-neighbour search algorithms.
  • Creating new dynamic or hierarchical clustering algorithms (e.g. based on spectral clustering or DBSCAN).
  • Creating dynamic algorithms for numerical linear algebra. For example, maintaining the PCA of a dynamically changing dataset.
  • Any other project in the area of algorithmic data science and machine learning.

Applicants should have a strong interest in the mathematical analysis of algorithms, knowledge of topics in discrete mathematics and linear algebra, and some familiarity with existing algorithms for data analysis and machine learning. Strong programming skills would also be desirable.

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 Peter Macgregor with an outline proposal.

Full instructions for the formal application process

The deadline for applications is 1 March 2025.

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/.

PGR Seminar with Daniel Wyeth and Ferdia McKeogh

The next PGR seminar is taking place this Friday 15th November at 2PM in JC 1.33a

Below is a Title and Abstract for Daniel’s and Ferdia’s talks – Please do come along if you are able.

Daniel:

Deep Priors: Integrating Domain Knowledge into Deep Neural Networks

Deep neural networks represent the state of the art for learning complex functions purely from data.  There are however problems, such as medical imaging, where data is limited, and effective training of such networks is difficult.  Moreover, this requirement for large datasets represents a deficiency compared to human learning, which is able harness prior understanding to acquire new concepts with very few examples.  My work looks at methods for integrating domain knowledge into deep neural networks to guide training so that fewer examples are required.  In particular I explore probabilistic atlases and probabilistic graphical models as representations for this prior information, architectures which enable networks to use these, and the application of these to problems in medical image understanding.

Ferdia:

“Lessons Learned From Emulating Architectures”

Automatically generating fast emulators from formal architecture specifications avoids the error-prone and time-consuming effort of manually implementing an emulator. The key challenge is achieving high performance from correctness-focused specifications; extracting relevant functional semantics and performing aggressive optimisations. In this talk I will present my work thus far, and reflect on some of the unsuccessful paths of research.

Doughnuts will be available! 🍩

PGR Seminar with Ariane Hine

The PGR seminars for this academic year are beginning this Friday 8th November at 2PM in JC 1.33A/B

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

Title: Enhancing and Personalising Endometriosis Care with Causal Machine Learning

Abstract: Endometriosis poses significant challenges in diagnosis and management due to the wide range of varied symptoms and systemic implications. Integrating machine learning into healthcare screening processes can significantly enhance and optimise resource allocation and diagnostic efficiency, and facilitate more tailored and personalised treatment plans. This talk will discuss the potential of leveraging patient-reported symptom data through causal machine learning to advance endometriosis care and reduce the lengthy diagnostic delays associated with this condition.

The goal is to propose a novel personalised non-invasive diagnostic approach that understands the underlying causes of patient symptoms and combines health records and other factors to enhance prediction accuracy, providing an approach that can be utilised globally.

Fudge donuts will be available! 🍩

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.

Fully-funded PhD scholarship in parallel programming and dependent-types

The school of Computer Science at the University of St Andrews has a fully-funded scholarship available working in the Programming Languages Research Group with Dr Christopher Brown. Applications must be received by 1 March 2025.

Background

Algorithmic skeletons provide a convenient and high-level approach to writing efficient parallel software by leveraging common patterns of parallel behaviours. A skeleton library presents the programmer with a library of high-level parallel interfaces, abstracting away the low-level complexities of manually handling concurrency primitives, e.g. locking, synchronisation and thread creation. Skeletons give an excellent compromise between ease of programming and the ability to generate highly efficient parallel software. A wide range of skeletons have been developed for several different languages, including Fastflow, TBB, PPL and OpenMP. However, despite the proliferation of skeleton libraries, there is little support for an increasingly popular class of programming languages equipped with dependent types.

 

Dependently-typed programming languages address the problem of program safety by ensuring that code conforms to its specification. This is achieved by permitting types to depend on values, thereby allowing programmers to express logical properties, and proof, as intrinsic parts of their programs. This conformance is checked at compile-time. This interest in dependent-types has resulted in a number of functional languages such as pi-forall, Agda, Idris and Coq. However, despite these developments in types, these dependently-typed languages still lack a parallel implementation, making development of safe parallel programs impossible.

 

This project will explore approaches to designing and implementing a dependently-typed parallel programming language. These approaches will consider the technical challenges, but also balancing those with the high-level usability that skeletons bring and the performance expectations of a performant system. As part of this exploration, use-cases will also need to be developed, and the scientific evaluation of the performance of the system will need to be carried out.

Topics of Interest

This project is largely exploratory in nature, and may take several different approaches and directions, including (but not limited to):

  • Extending an existing dependently-typed language, such as Idris, with new concurrency primitives.
  • Designing and implementing an efficient parallel runtime system as a backend to the language.
  • Building on top of these primitives to provide dependently-typed concurrency behaviours, such as synchronisation points, channel behaviours, etc.
  • To design and implement a set of dependently-typed algorithmic skeletons such as farms and pipelines.
  • To explore and identify new skeletons that arise from writing dependently-typed programs.
  • To use dependent-types to encode safety and soundness properties and reason about these properties in a formal way.

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 Chris. 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.

 

PhD studentships available for 2025 entry

The School of Computer Science at the University of St Andrews is offering a number of PhD scholarships for 3.5 years of study in our doctoral research programme. UK, EU and International students are all eligible for fully-funded scholarships consisting of tuition and a stipend. These awards are part-funded through the University of St Andrews’ ‘handsel’ scheme for tuition waivers.

The School of Computer Science is a centre of excellence for computer science teaching and research, with staff and students from Scotland and all parts of the world. It is a member of the Scottish Informatics and Computer Science Alliance (SICSA).

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).

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.

Application Deadline

All applications received before 1st February 2025 will be considered for these scholarships.

How to Apply

Any PhD application received by the deadline will be automatically considered for these scholarships. There is no need for a separate application.

The School’s main research themes are Artificial Intelligence, Health Informatics, Human-Computer Interaction, Programming Languages, and Systems. You can find further details at https://www.st-andrews.ac.uk/computer-science/research/themes/. In addition, we have cross-cutting research groups in Complex and Adaptive Systems, Computer Vision, Constraints, Data Science, MedTech, Research Software, and Responsible Computing. Applicants with interests in any of these areas are encouraged to develop a relevant research proposal and apply.

The best way to obtain a place and a scholarship is to make a robust PhD application. You are strongly encouraged to read the application guidance written on our webpages. Note that this guidance asks you to approach supervisors before formal submission to discuss your project ideas with them. Historically, applications with no named supervisor have been much less likely to result in an offer. We provide a list of existing faculty, areas of research and some potential project ideas. All supervisors listed on this page may be contacted directly to discuss possible projects. You can define your own project or discuss a project currently on offer.

Full application instructions can be found at https://www.st-andrews.ac.uk/computer-science/prospective/pgr/how-to-apply/. Enquiries and questions may be directed to pg-admin-cs@st-andrews.ac.uk.