On behalf of the school, we would like to congratulate Di Wu supervised by Blesson Varghese, who has passed his PhD viva with minor corrections.
Thanks to Professor Graham Kirby who was internal examiner and Dr Chris Anagnostopoulos from Glasgow as external examiner.
This years Distinguished Lecture series was delivered yesterday ( Tuesday 12th March) by Professor Neil Lawrence, University of Cambridge
In his talk on, ‘The Atomic Human Understanding Ourselves in the Age of AI’ he gave an overview of where we are now with machine learning solutions, and what challenges we face both in the near and far future. These include the practical application of existing algorithms in the face of the need to explain decision-making, mechanisms for improving the quality and availability of data and dealing with large unstructured datasets.
Today the School of Computer Science Equality, Diversity, and Inclusion Committee held an International Snack event. This event aimed to bring together our international staff and students for an informal gathering and share some snacks from around the globe.
£100m boost in AI research will propel transformative innovations – UKRI
We are delighted to participate in the National Edge AI Hub that is funded by UKRI. The Hub comprises 12 universities and numerous industry and public sector organisations. The vision of the Hub is to develop the underlying research to secure the edge of the network using Artifical Intelligence / Machine Learning (AI/ML).
The St Andrews team led by Dr Blesson Varghese will develop fundamental research on making AI/ML algorithms and models to work on extremely small devices in challenging environments for critical decision making.
Dr Varghese said, “We are delighted to be a part of this national initiative and contribute to the vision of making Edge AI a reality for times when it is most needed – mitigating cyber threats on our digital infrastructure”.
Dr Varghese directs the Edge Computing Hub at the University of St Andrews.
On 11th April, the School of Computer Science at St Andrews will host our Doors Open event. We will be thrilled to welcome any and all visitors from outwith the School, whether you are locally based, from elsewhere in the UK, or from overseas.
As a rapidly growing school, we are looking to build relationships with new partners and are keen to find out how we can help you, your companies, and/or organisations to solve problems and improve processes.
Our Doors Open Day will have over 60 individual exhibits and activities. Our presenters will be our staff and students, with representation from 1st year undergrad through to PhD students, academic and technical members of staff.
Please register here if you would like to attend to enable us to order sufficient food!
We look forward to welcoming Prof Neil Lawrence, Cambridge who will talk about ‘The Atomic Human: Understanding Ourselves in the Age of AI’.
A vital perspective is missing from the discussions we are having about Artificial Intelligence: what does it mean for our identity?
Our fascination with AI stems from the perceived uniqueness of human intelligence. We believe it is what differentiates us. Fears of AI not only concern how it invades our digital lives but also the implied threat of an intelligence that displaces us from our position at the centre of the world.
Atomism, proposed by Democritus, suggested it was impossible to continue dividing matter down into ever smaller components: eventually, we reach a point where a cut cannot be made (the Greek for uncuttable is ‘atom’). In the same way, by slicing away at the facets of human intelligence that can be replaced by machines, AI uncovers what is left: an indivisible core that is the essence of humanity.
By contrasting our own (evolved, locked-in, embodied) intelligence with the capabilities of machine intelligence through history, The
Atomic Human reveals the technical origins, capabilities, and limitations of AI systems, and how they should be wielded. Not just
by the experts, but by ordinary people. Either AI is a tool for us, or we become a tool of AI. Understanding this will enable us to choose
the future we want.
This talk is based on Neil’s forthcoming book to be published with Allen Lane in June 2024. Machine learning solutions, in particular
those based on deep learning methods, form an underpinning of the the current revolution in “artificial intelligence” that has dominated
popular press headlines and is having a significant influence on the wider tech agenda.
In this talk, I will give an overview of where we are now with machine learning solutions, and what challenges we face both in the
near and far future. These include practical application of existing algorithms in the face of the need to explain decision-making,
mechanisms for improving the quality and availability of data, dealing with large unstructured datasets.
As part of their efforts to enhance privacy and trust on the Web, many applications need to be able to determine whether or not a relationship exists between different entities. For example, it is desirable for web browsers to be able to determine that two domain names are under the same administrative control, such that cookies and other data can be safely shared between them. While determining these relationships might be easy for humans, it is impossible to do so algorithmically.
This project will explore approaches to the defining and enforcing organisational boundaries on the Internet. These approaches will consider the technical challenges, balancing those with user behaviour and expectations, and regulatory considerations. This will include identifying use cases, evaluating and measuring existing and proposed approaches, and developing and implementing novel techniques. Where appropriate, this will involve engagement with standards development organisations, including the World Wide Web Consortium (W3C) and the Internet Engineering Task Force (IETF). Continue reading
We would like to invite our graduating students and their guests to join us for a celebration in honour of their achievements. Please join us for a small reception with a glass of bubbly and some Fisher and Donaldson’s cakes.
The event will take place on Tuesday, November 28th, between 12 noon and 2 p.m. at the Jack Cole coffee area.
We look forward to commemorating this special occasion together.
The School of Computer Science at the University of St Andrews is offering a number of PhD studentships for 3.5 years of study in our doctoral programme. Funding is available to cover tuition fees for UK, EU and international students, as well as living expenses (a stipend of £18,622 per annum, or the standard UKRI stipend if it is higher). We offer two types of studentship:
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).
We are looking for highly motivated research students willing to be part of a diverse and supportive research community. Applicants must hold a good BSc or MSc in Computer Science, or a related area appropriate for their proposed topic of study.
We especially encourage female applicants and underrepresented minorities to apply. The University of St Andrews is committed to promoting equality of opportunity for all, which is further demonstrated through its working on the Gender and Race Equality Charters and being awarded the Athena SWAN award for women in science, HR Excellence in Research Award and the LGBT Charter.
1st February 2024.
Any PhD application received through the University PGR application system by the deadline will be automatically considered for these studentships. There is no need for a separate application. Note, however, that if you are applying for a CSC Scholarship then you cannot be considered for these School studentships due to conflicting application dates.
We strongly advise applicants to contact potential supervisors to discuss their research proposal before applying. Historically, applications with no named supervisor have been much less likely to result in an offer.
The School’s main research groups are Artificial Intelligence, Computer Systems, Human-Computer Interaction, and Programming Languages. You can find further details at https://www.st-andrews.ac.uk/computer-science/research/groups/. A list of existing faculty and areas of research can be found at https://www.st-andrews.ac.uk/computer-science/prospective/pgr/supervisors/. 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. Some highlighted potential areas or projects offered by supervisors include:
Full details on how to apply can be found at https://www.st-andrews.ac.uk/computer-science/prospective/pgr/how-to-apply/
Application enquiries can be directed to pg-admin-cs@st-andrews.ac.uk.
The School of Computer Science is looking to recruit a lecturer as part of a large on-going expansion of our academic staff and to support our evolving approach to digital teaching.
We wish to appoint a lecturer (either Education track, or Education and Research track) to join our vibrant teaching and research community, which is ranked among the top venues for Computer Science education and research worldwide. The School develops deep science and technology across the discipline of computer science, which informs and underpins our teaching at undergraduate, masters, and doctoral levels. We are expanding our teaching programmes to include digital modes of delivery to allow us to teach a broader range of students than would ever be able to physically move to St Andrews for the duration of a traditional programme.
The is an exciting departure that lets us take the School’s reputation for teaching excellence to an extended audience, including individuals seeking to upskill within employment, those seeking a career change, and those with other constraints on their time and location. In the first instance this will involve the development of an entirely new digital-only MSc programme in data science.
We are seeking dynamic, collegial individuals who value teaching and research excellence to support the expansion and development of our strengths in data and computational science centred around our Artificial Intelligence and Systems research groups. The right candidate will be able to contribute to research and teaching in an appropriate area – including, but not limited to, computational science, data analytics, machine learning for data interpretation, scientific visualisation – as well as being involved in the development and delivery of “born-digital” teaching resources and assessment methods sitting alongside more traditional approaches and materials.
Please see the linked advert for more information!
