Seminar – Nobuko Yoshida – Monday, 3 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! 🎉

 

Professor Stephen Linton Retirement

Colleagues from the University, past and present, gathered to say a fond farewell to Professor Stephen Linton who is retiring from the School at the end of 2024. Steve was a valuable and respected member of staff for 31 years and also a former Head of School and Director of CIRCA.

Steve was fundamental in building our collaboration with colleagues in the School of Mathematics and Statistics, serving as Director of the Centre of Interdisciplinary Research in Computational Algebra (CIRCA) for many years. CIRCA has been the platform for nearly 25 years of fruitful collaboration between the two Schools, producing an internationally recognised body of work spanning both research papers and software. Steve played a central role in building and sustaining the Centre, supporting it with a substantial EPSRC Platform Grant in 2010.

As Head of School, Steve was always generous in helping those around him progress, even allowing staff to study for a law degree during research leave!

Below are some tributes from colleagues/friends:-

Professor Ian Gent: “Steve is one of those programmers who is 10 times better than other people who are themselves really good programmers.  The story of one of the coffee area’s Go boards illustrates this.   The school hosted an afternoon programming competition open to teams of 3.   Steve entered by himself having been assured that his favourite programming language GAP was available.  When that turned out to be wrong he just used C instead.  And then very comfortably won the programming competition solving more problems than any of the groups of three.  A Head of School, he didn’t want to benefit personally from the prize so bought the school a Go board.
Nobody will argue with the statement that the smartest person in the school is retiring.  When I used to research with him, people often asked me how I coped with working with somebody so ridiculously clever. My reply was “because I’m working WITH him” the advantage being that you weren’t competing!   A classic example of this was when we had a paper rejected because reviewers didn’t think the work was novel despite depending on amazing algorithms Steve had coded up.  In making sure the revision emphasised the novelty, Steve said “But any one of two dozen people could have done it” and I said “Yes and if any one of them had done, it would have been novel!”   The revised paper got accepted and has just hit 100 citations on Google Scholar.”

Professor Tom Kelsey: “Steve, Ian Gent and I – had a research meeting with Colva Roney-Dougal at which we agreed that there were two distinct coding tasks, one for Steve, the other for Ian and me, both quite challenging. Ian and I started work on the whiteboard outside Steve’s office, planning how we might go about writing and evaluating our code. After 25 minutes detailed discussion, we’d made good progress and had the kernel of a plan that would give us plenty of work for the rest of the week. Steve came out of his office having finished his task in one short attempt – the resulting paper used this code without revision. Ian and I felt like a pair of numbskulls.

On a more personal note, I was Steve’s first PhD student. During my studies one of my daughters became quite unwell, and dealing with her complex treatments and the other four children didn’t leave much time for my Doctoral studies. Steve was incredibly supportive, dealing with the School and University in such a way that all I had to worry about was my daughter’s wellbeing. When I returned I was still very much focussed on family issues, but Steve guided me expertly and kindly through the rest of my studies. For which I am eternally grateful.”

Professor Graham Kirby: “Steve is compassionate and understanding. I was a newish DoT at a time when my wife was seriously ill, and I was responsible for writing the school’s institutional teaching review document. As HoS, Steve found ways to alleviate the real or perceived pressure on me, enabling me to focus on family.”

Professor Chris Jefferson: “Steve also contributed to many major research projects, in particular GAP. GAP is a mathematics system, which has been actively developed since 1988.  While GAP is maintained by academics from around the world, St Andrews computing and mathematics, led by Steve, took over the leadership of GAP from RWTH Aachen in 1997, and lead GAP until 2022. In that time, many students and academics at St Andrews have been involved with GAP.”

Professor Karen Petrie (University of Dundee and University of St Andrews graduate 2000): “Steve has had a very lasting impression on me from my UG days when he was my tutor. I first met him in 1st year in C programming tutorials. I remember having my first ever memory leak in those days and Steve making all the hours which I spent fixing it better when he told me ‘now you are a computer sciemtist’. He also taught me the difference between P and NP, I remember being amazed to learn that P vs NP was an open problem, the very idea of open problems was new to me and incredibly exciting but challenging. He was also extremely compassionate I remember in my 4th year I had tonsillitis and Steve asked me why I was in University and sent me home to bed. He told me he did not want to see me until I could speak again! One of the amazing things about Steve is his practical coding ability and his theoretical ability as a student he felt like the rock star of CS, that impression of him has never changed. This means a kind word from him means a lot as we all want to emanate him. As an example as a PhD student we were working on a joint research paper as research does, it was not going well, so we were debugging code together. It had been a long trying day. Steve made it all better by telling me ‘you now debug code as well as I do’. Now, I am a professor myself and I try to do the same for my students as Steve did for me: to challenge them when appropriate, to be compassionate when that is what they need but most importantly always to treat them as an equal. I feel incredibly fortunate to be able to call Steve not just a mentor, nor a collaborator but a friend.”

All at CS would like to wish Steve a long and happy retirement 🎉

Alex Bain (School Manager), Professor Steve Linton, Professor Ian Miguel (Head of School) 

Professor Ian Miguel (HoS) and Professor Ron Morrison (former HoS) 

Dr Tristan Henderson, Professor Steve Linton 

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.

AI Seminar Wednesday 27th November – Lars Kotthoff

We have another exciting AI seminar coming up on Wednesday 27th November at 1pm.

This time our speaker is an alumnus!

When? 27/11/24, 1pm

Where? JCB 1.33B

Who? Lars Kotthoff

Lars Kotthoff is the Templeton Associate Professor of Computer Science, Founding Adjunct Faculty at the School of Computing, and a Presidential Faculty Fellow at the University of Wyoming. His research in foundational AI and Machine Learning as well as applications of AI in other areas (in particular Materials Science) has been widely published and recognized. Lars is a senior member of the Association for the Advancement of AI and the Association of Computing Machinery.

What?

Title: AI for Materials Science: Tuning Laser-Induced Graphene Production

Abstract: AI and machine learning have advanced the state of the art in many application domains. We present an application to materials science; in particular, we use surrogate models with Bayesian optimization for automated parameter tuning to optimize the fabrication of laser-induced graphene. This process allows to create thin conductive lines in thin layers of insulating material, enabling the development of next-generation nano-circuits. This is of interest for example for in-space manufacturing. We are able to achieve improvements of up to a factor of two compared to existing approaches in the literature and to what human experts are able to achieve, in a reproducible manner. Our implementation is based on the open-source mlr and mlrMBO frameworks and generalizes to other applications.