Abstract:

Tissue ablation is a widely used treatment in both the cosmetic and medical sectors, for treating various diseases or to improve cosmetic outlooks. We present our tissue ablation model which can predict the depth of ablation, and the surrounding thermal damage caused by the laser during ablation.

“Non-diffracting” beams have a multitude of uses in physics, from optical manipulation to improved microscopy light sources. For the first time we show that these beams can be modelled using Monte Carlo radiation transport method. Allowing better insight into how these beams propagate in a turbid medium.

Both of these projects use the Monte Carlo radiation transport method (MCRT) to simulate light transport. The MCRT method is a powerful numerical method that can solve light transport though heavily scattering and absorbing mediums, such as biological tissues. The method is extremely flexible and can model arbitrary geometries and light sources. MCRT can also model the various micro-physics of the simulated medium, such as polarisation, fluorescence, and Raman scattering. This talk will give an overview of our group’s work, with particular focus on simulating tissue ablation, and modelling “non-diffracting” beams.

Speaker Bio:

Lewis McMillan is a final year physics PhD student at St Andrews University. His research interests are in using Monte Carlo radiation transport method for various applications within medicine and biophotonics.

This is joint work with Charlie Blake.

Abstract:

The most famous single-player card game is ‘Klondike’, but our ignorance of its winnability percentage has been called “one of the embarrassments of applied mathematics”. Klondike is just one of many single-player card games, generically called ‘solitaire’ or ‘patience’ games, for which players have long wanted to know how likely a particular game is to be winnable for a random deal. A number of different games have been studied empirically in the academic literature and by non-academic enthusiasts.

Here we show that a single general purpose Artificial Intelligence program, called “Solvitaire”, can be used to determine the winnability percentage of approximately 30 different single-player card games with a 95% confidence interval of ± 0.1% or better. For example, we report the winnability of Klondike to within 0.10% (in the ‘thoughtful’ variant where the player knows the location of all cards). This is a 30-fold reduction in confidence interval, and almost all our results are either entirely new or represent significant improvements on previous knowledge.

Speaker Bio:

Ian Gent is professor of Computer Science at the University of St Andrews. His mother taught him to play patience and herself showed endless patience when he “helped” her by taking complete control of the game. A program to play a patience game was one of the programs he wrote on his 1982 Sinclair Spectrum now on the wall outside his office.

Abstract:

This talk is an overview of the VAMPIRE (Vessel Assessment and Measurement Platform for Images of the REtina) project, an international and interdisciplinary research initiative created and led by the Universities of Dundee and Edinburgh in Scotland, UK, since the early 2000s. VAMPIRE research focuses on the eye as a source of biomarkers for systemic diseases (e.g. cardiovascular, diabetes, dementia) and cognitive decline, as well as on eye-specific diseases. VAMPIRE is highly interdisciplinary, bringing together medical image analysis, machine learning and data analysis, medical research, and data governance and management at scale. The talk introduces concisely the aims, structure and current results of VAMPIRE, the current vision for effective translation to society, and the several non-technical factors complementing technical research needed to achieve effective translation.

Speaker Bio:

Emanuele (Manuel) Trucco, MSc, PhD, FRSA, FIAPR, is the NRP Chair of Computational Vision in Computing, School of Science and Engineering, at the University of Dundee, and an Honorary Clinical Researcher of NHS Tayside. He has been active since 1984 in computer vision, and since 2002 in medical image analysis, publishing more than 270 refereed papers and 2 textbooks, and serving on the organizing or program committee of major international and UK conferences. Manuel is co-director of VAMPIRE (Vessel Assessment and Measurement Platform for Images of the Retina), an international research initiative led by the Universities of Dundee and Edinburgh (co-director Dr Tom MacGillivray), and part of the UK Biobank Eye andVision Consortium. VAMPIRE develops software tools for efficient data and image analysis with a focus on multi-modal retinal images. VAMPIRE has been used in UK and international biomarker studies on cardiovascular risk, stroke, dementia, diabetes and complications, cognitive performance, neurodegenerative diseases, and genetics.

Abstract:

The Carpentries (https://carpentries.org/) is a global community of
volunteers which teach foundational coding and data science skills to researchers
worldwide through Software Carpentry, Data Carpentry, and Library Carpentry
workshops. Being involved in the Carpentries since 2015, I organised and taught
at several workshops, developed new lessons, and trained new Carpentry instructors.
In my talk I will discuss the Carpentries pedagogical approach, and also consider
its applicability to teaching Computer Science students.

Abstract:

2016 was a weird year for Carron. On the plus side she was one of twelve women in Computing and Mathematics to receive a Suffrage Science Award, recognising both scientific achievement and ability to inspire others. She’s involved in lots of work to promote careers in science for women, having initiated and led the Athena SWAN programme of actions at Stirling for four years, and started building Cygnets: a good practice network of UK computing departments engaged in gender equality work. But 2016 was also one of the worst years of her life, with lots of stress, and consequent depression. She’ll talk about her journey from student to professor, with some thoughts about the people and qualities that lead to success, and how those qualities can also be enemies. This should be relevant for everyone, no matter their career stage, academic or professional services, or discipline. (Spoiler alert: she will probably have more questions than answers in this talk!)

Speaker Bio:

Carron Shankland is a professor in Computing Science at the University of Stirling. Her research is about understanding the behaviour of biological systems through mathematical and computational models. Current projects include using data mining to understand disease dynamics, and modelling cancer therapies to try to understand how the actions of therapies might combine to greater effect. As a senior academic, she believes in participating in governance: she’s had positions on Academic Council and University Court, and was deputy head of Natural Sciences. Carron is passionate about the promotion of careers in science for women, having initiated and led the Athena SWAN programme of actions at Stirling 2012-2016. She chairs the BCS Women in Computing Research Group and is building DiVERct: a good practice network of ICT (computing and electronic and electrical engineering) departments engaged in diversity and inclusion work. In 2017 she won one of the first Scottish Women’s Awards for services to science and technology, and in 2016 she was one of twelve women in Computing and Mathematics to receive a Suffrage Science Award, recognising both scientific achievement and ability to inspire others. When she’s not doing computing science (or admin!) she likes to play classical chamber music (she plays clarinet and viola), chop things down in the garden, or visit galleries and coffee shops with her partner Pat (they’ve had a civil partnership since 2006).

Abstract:

This talk will concentrate on some successful applications of search-based and neural network algorithms in two distinctly different areas of real-time embedded systems development: scheduling and timing analysis, and Internet of Things. However it will then motivate some significant challenges for the artificial intelligence community that surprised a user from another research community. The talk will highlight how a seemingly simple-to-use powerful solutions would benefit from a more traditional engineering lifecycles.

Speaker Bio:

Dr Iain Bate is a Reader within the Real-Time Systems (RTS) Research Group at York. His main interests include scheduling and timing analysis, and design assurance to achieve dependable operation even when there are complex failures. His original doctoral work on scheduling and timing analysis was first patented and then adopted by Rolls-Royce for use on current aircraft projects. His work on timing analysis has been used on a large fast jet project.

Recently he has worked on applying the principles of Dependable Real-Time Systems (DRTS) to more complex systems such as automotive systems and Wireless Sensor Networks (WSN) including for environmental monitoring. In particular he has concentrated on producing models of aspects of systems through the building of systematic methods based around multi-variate statistical models. Dr Bate has published over 100 papers and 30 industrial reports, and secured and managed over £5 million worth of grants. He was the Editor-in-Chief for the Journal of Systems Architecture for 10 years.