Event

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! 🍩

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! 🍩

AI Seminar Friday 18th October – Leonardo Bezerra

The School is hosting an AI seminar on Friday 18th October at 11.30am in JCB1.33A!

Our speaker is Leonardo Bezerra from the University of Stirling.

FAIRTECH by design: assessing and addressing the social impacts of artificial intelligence systems

In a decade, social media and big data have transformed society and enabled groundbreaking artificial intelligence (AI) technologies like deep learning and generative AI. Applications like ChatGPT have impacted the world and outpaced regulatory agencies, who were rushed from a data-centred to an AI-centred concern. Recent developments from both the United Kingdom (UK) and the United States (US) originated in the executive branch, and the most advanced Western binding legislation is the European Union (EU) AI Act, expected to be implemented over the next three years. In the meantime, the United Nations (UN) have proposed an AI advisory body similar to the International Panel on Climate Change (IPCC), and countries from the Global South like Brazil are following Western proposals. In turn, AI companies have been proactive in the regulation debate, aiming at a scenario of improved accountability and reduced liability. In this talk, we will briefly overview efforts and challenges regarding AI regulation and how major AI players are addressing it. The goal of the talk is to stir future project collaborations from a multidisciplinary perspective, to promote a culture where the development and adoption of AI systems is fair, accountable, inclusive, responsible, transparent, ethical, carbon-efficient, and human-centred (FAIRTECH) by design.

Speaker bio: Leonardo Bezerra joined the University of Stirling as a Lecturer in Artificial Intelligence (AI)/Data Science in 2023, after having been a Lecturer in Brazil for the past 7 years. He received his Ph.D. degree from Université Libre de Bruxelles (Belgium) in 2016, having defended a thesis on the automated design of multi-objective evolutionary algorithms. His research experience spans from applied data science projects with public and private institutions to supervising theses on automated and deep machine learning. Recently, his research has concentrated on the social impact of AI applications, integrating the Participatory Harm Auditing Workbenches and Methodologies project funded by Responsible AI UK.

Constraint Programming research group at the CP2024 conference

The 30th International Conference on Principles and Practice of Constraint Programming (CP2024) was held in Girona, Catalonia during the first week of September. The CP conference series are the main event for researchers in constraint programming to get together, share latest developments and for networking. 

Our School contributed to the conference in large numbers this year. 

  • Ian Gent was the invited speaker on the conference’s first day, with his talk entitled “Solving Patience and Solitaire Games with Good Old Fashioned AI” (abstract) (video recording).  
  • Christopher Stone was invited to the discussion panel ‘Have Chatbots Reached the Holy Grail?’ at the same workshop and presented the paper: Ian Miguel, András Z. Salamon, Christopher Stone, Automating Reformulation of Essence Specifications via Graph Rewriting (paper) 
  • Özgür Akgün was the Diversity, Equity and Inclusion chair of the conference and presented the DEI initiatives to all the attendees (video recording).
  • We presented several papers at ModRef 2024, the 23rd workshop on Constraint Modelling and Reformulation: 
  • Csobán Balogh, Ruth Hoffmann and Joan Espasa, Towards Understanding Differences Between Modelling Pipelines: a Modelers Perspective (paper) (slides) 
  • Joan Espasa Arxer, Ian Gent, Ian Miguel, Peter Nightingale, András Z. Salamon and Mateu Villaret, Cross-Paradigm Modelling: A Case Study of Puzznic (paper) 
  • Carla Davesa Sureda, Joan Espasa Arxer, Ian Miguel and Mateu Villaret Auselle, Towards High-Level Modelling in Automated Planning (paper)
  • Nguyen Dang, Ian Gent, Peter Nightingale, Felix Ulrich-Oltean and Jack Waller, Constraint Models for Relaxed Klondike Variants (paper) (slides)
    • Jack Waller (who is an undergraduate student at St Andrews!) presented this work.
  • Alessio Pellegrino, Özgür Akgün, Nguyen Dang, Zeynep Kiziltan and Ian Miguel, Automatic Feature Learning for Essence: a Case Study on Car Sequencing (paper) (slides) 
    • Alessio Pellegrino (who is a visiting student from University of Bologna) presented this work.
  • Orhan Yigit Yazicilar, Özgür Akgün and Ian Miguel, Automated Nogood-Filtered Fine-Grained Streamlining: A Case Study on Covering Arrays (paper) 
  • Our PhD students Orhan Yigit Yazicilar, Erdem Kus, Carla Devesa Sureda, and Joseph Loughney attended the doctoral program. As part of the doctoral program they presented their work by giving a talk and presenting a poster. In addition, they were assigned a mentor during the conference. 
  • Visiting research student (from University of Bologna) Alessio Pellegrino gave his first talk at the ModRef 2024 workshop. 
  • PhD student Erdem Kus presented the following paper in the technical track of the main conference: 
  • Erdem Kuş, Özgür Akgün, Nguyen Dang, and Ian Miguel, Frugal Algorithm Selection (slides) (video recording)

Finally, here is a group photo of the St Andrews group, standing at the front steps of the beautiful conference venue in Girona. 

Week 1 Social Events

The following social events are being held in the School this week in the Jack Cole coffee area:-

  • Monday 16 September – 17:00 – 18:00 – MSc and MSci welcome reception (TODAY)
  • Wednesday 18 September – 16:00 – 17:00 – Honours (Junior & Senior) welcome reception
  • Friday 20 September – 17:00 – 18:00 – Sub-honours (students on first and second years of CS programmes) social event

Drinks 🍷 and snacks 🍰 available at all events, so please come along and join us!

STACS Welcome BBQ 🍔

If you are a new Undergraduate or Postgraduate Taught student to the School of Computer Science, you are invited to the STACS Welcome BBQ outside the Jack Cole Coffee Area on Friday 13th September 5.30pm-7.30pm.

The usual BBQ favourites will be available from the grill and refreshments will be provided. We look forward to seeing you there!