The AI research theme members came together in an internal event on Tuesday 6 June. We discussed our latest projects, shared our insights and challenges, and brainstormed new ideas for future research. It was a great opportunity to connect with our colleagues and learn from each other.
We look forward to more opportunities to collaborate and grow as an AI group.
A fully-funded PhD scholarship is available to support an exceptional student wishing to undertake doctoral research in health informatics, in particular looking at analysing and predicting disease trajectories of multimorbidity. This prestigious PhD scholarship is awarded by St Leonard’s Postgraduate College at the University of St Andrews and will be supervised by Dr Areti Manataki, Dr Katherine Keenan, Prof Colin McCowan and Dr Michail Papathomas. Applications must be received by 12 June 2023.
Further information, including how to apply, can be found at: https://www.st-andrews.ac.uk/study/fees-and-funding/scholarships/scholarships-catalogue/postgraduate-scholarships/world-leading-scholarship-04-computer-science-medicine-geography/
A fully-funded PhD scholarship in Computer Science is available for a strong and motivated student wishing to work at the intersection of vision, large-language models, and robotic planning. This prestigious PhD scholarship is awarded by St Leonard’s Postgraduate College at the University of St Andrews and will be supervised by Dr Juan Ye, Dr Alice Toniolo, and Dr Kasim Terzic.
For more information, including how to apply, please see the advert: https://www.st-andrews.ac.uk/study/fees-and-funding/scholarships/scholarships-catalogue/postgraduate-scholarships/world-leading-scholarship-01-computer-science/?
This fully-funded position will aim to improve both the modelling capabilities and the solving performance when confronting Automated Planning problems. We seek motivated candidates with a strong background in Computer Science, with excellent programming skills and some previous knowledge and experience in solving combinatorial optimisation problems.
Please take a look at the instructions on on how to apply.
The University of St Andrews is the top university in Scotland and second in the UK in The Times and Sunday Times Good University Guide 2023. Last year St Andrews was ranked number one in the UK, the first time in the near 30-year history of the Guide, or any UK ranking, that any university has been placed above those of Oxford and Cambridge.
If you are interested in either knowing more or have any informal enquiry, please do get in touch with Joan Espasa Arxer via email: jea20@st-andrews.ac.uk
The deadline for applications is the 1st of March 2023.
Research carried out by Charlie Blake and Ian Gent to compute the approximate odds of winning any version of solitaire features in Major Nelson’s Video Podcast [Interview with Ian and Charlie starts 23:56] for XBox news today.
Today is National Solitaire Day and the 30th anniversary of the game. The celebrations include an invitation to participate in a record breaking attempt at the most games of Microsoft Solitaire completed in one day. You can download the collection free or play it through your browser.
The Klondike Solitaire research also featured in the New Scientist last year.
Link to the full paper on arxiv: https://arxiv.org/abs/1906.12314
Online article published in Technology Nov 17th 2019: https://www.newscientist.com/article/2223643-we-finally-know-the-odds-of-winning-a-game-of-solitaire/
Abstract: In this talk, I will present a case study to illustrate how automated algorithm configuration can be used to gain insights into theoretical results on an evolutionary algorithm, namely the (1+(λ,λ)) Genetic Algorithm. This work is a collaboration with Carola Doerr.
The (1+(λ,λ)) Genetic Algorithm is an evolutionary algorithm that has interesting theoretical properties. It is the first algorithm where the benefit of crossover operator is rigorously proved. It is also the first example where self-adjusting parameter choice is proved to outperform any static parameter choice. However, it is not very well understood how the hyper-parameter settings influences the overall performance of the algorithm. Analyzing such multi-dimensional dependencies precisely is at the edge of what running time analysis can offer. In this work, we make a step forward on this question by presenting an in-depth study of the algorithm’s hyper-parameters using techniques in automated algorithm configuration.
Speaker bio: Dr Nguyen Dang is a post-doc in the Constraint Programming group at the University of St Andrews. Her main research focus is on automated algorithm configuration, algorithm selection and their applications in various contexts. These techniques make use of statistical methods and machine learning for fine-tuning of algorithm parameters, assessing parameters’ importance and building algorithm portfolios. Another line of her research is about solving combinatorial optimisation problems using metaheuristic algorithms.
Research carried out by Charlie Blake and Ian Gent to compute the approximate odds of winning any version of solitaire featured in New Scientist last week (print edition November 23rd ). Ian emphasised the calibre of research carried out by our undergraduate students and his early interaction with card games.
“This research has been hugely satisfying to me because my mother taught me games like King Albert as a child and I loved to play them with her. Now I know for the first time the chance of winning that game is about 68.5%.
It is wonderful to see work which started as an undergraduate student project feature in the New Scientist. This obviously reflects Charlie’s fantastic programming that he did. But it also shows the research-level quality work that undergraduate students can do as part of their studies in St Andrews.”
Link to the full paper on arxiv: https://arxiv.org/abs/1906.12314
Online article published in Technology Nov 17th: https://www.newscientist.com/article/2223643-we-finally-know-the-odds-of-winning-a-game-of-solitaire/
The Melville Trust for the Care and Cure of Cancer have funded a PGR Studentship relative to the project entitled ‘Detecting high-risk smokers in Primary Care Electronic Health Records: An automatic classification, data extraction and predictive modelling approach’.
The supervisors are Prof. Frank Sullivan of the School of Medicine and Prof. Tom Kelsey of the School of Computer Science, with work commencing in September 2019. The award is for £83,875.
Can a user write a good MIP model without understanding linearization? Modelling languages such as AMPL and AIMMS are being extended to support more features, with the goal of making MIP modelling easier. A big step is the incorporation of predicates, such a “cycle” which encapsulate MIP sub-models. This talk explores the impact of such predicates in the MiniZinc modelling language when it is used as a MIP front-end. It reports on the performance of the resulting models, and the features of MiniZinc that make this possible.
Professor Mark Wallace is Professor of Data Science & AI at Monash University, Australia. We gratefully acknowledge support from a SICSA Distinguished Visiting Fellowship which helped finance his visit.
Professor Wallace graduated from Oxford University in Mathematics and Philosophy. He worked for the UK computer company ICL for 21 years while completing a Masters degree in Artificial Intelligence at the University of London and a PhD sponsored by ICL at Southampton University. For his PhD, Professor Wallace designed a natural language processing system which ICL turned into a product. He moved to Imperial College in 2002, taking a Chair at Monash University in 2004.
His research interests span different techniques and algorithms for optimisation and their integration and application to solving complex resource planning and scheduling problems. He was a co-founder of the hybrid algorithms research area and is a leader in the research areas of Constraint Programming (CP) and hybrid techniques (CPAIOR). The outcomes of his research in these areas include practical applications in transport optimisation.
He is passionate about modelling and optimisation and the benefits they bring. His focus both in industry and University has been on application-driven research and development, where industry funding is essential both to ensure research impact and to support sufficient research effort to build software systems that are robust enough for application developers to use.
He led the team that developed the ECLiPSe constraint programming platform, which was bought by Cisco Systems in 2004. Moving to Australia, he worked on a novel hybrid optimisation software platform called G12, and founded the company Opturion to commercialise it. He also established the Monash-CTI Centre for optimisation in travel, transport and logistics. He has developed solutions for major companies such as BA, RAC, CFA, and Qantas. He is currently involved in the Alertness CRC, plant design for Woodside planning, optimisation for Melbourne Water, and work allocation for the Alfred hospital.
