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Computing Science and Maths Seminars, 2018/2019

Spring 19 image

Seminars will take place in Room 4B96,  Cottrell Building, University of Stirling. Normally, from 15.00 to 16.00 on Friday afternoons during semester time, unless otherwise stated. For instructions on how to get to the University, please look here.

If you would like to give a seminar to the department in future or if you need more information,  
please contact the seminar organisers, Dr. Sandy Brownlee ( and Dr. Wen-shin Lee (

Spring 2019

Date Speaker Title/Abstract
18th January
Lucia Vadicamo, Graduate Fellow, Institute of Information Science and Technologies, Pisa Improving Metric Search through Finite Isometric Embeddings

Metric search is concerned with the efficient evaluation of proximity queries in metric spaces. Most metric indexing and searching mechanisms rely upon the triangle inequality property. This property allows deriving bounds on the distance between data objects, which are used to efficiently exclude partitions of the data that do not contain solutions to a given query. This seminar will discuss a class of metric spaces meeting a stronger property, named n-point property, which is a condition defined in term of finite isometric embeddings into the Euclidean space. This property gives stronger geometric guarantees, in particular one named the Hilbert Exclusion property. Moreover, it can be used to embed metric objects into a finite-dimensional Euclidean space, which turns out to have implications not only for the similarity search but also for dimensionality reduction and data visualization tasks.

Lucia Vadicamo graduated in Mathematics at the University of Pisa, Italy, in 2013 and was awarded a PhD in Information Engineering at the University of Pisa, Italy, in 2018. Her current research interests involve content-based image retrieval, similarity search and permutation-based indexing.
25th January
Prof. Rachel Norman, CSM, University of Stirling The Professional Doctorate
(non-research talk)

This session is aimed at those who are potentially interested in doing the Professional Doctorate in Big Data Science. This is a more applied form of a PhD and can follow on from the MScs run in the division.

This talk is mainly aimed at MSc students and undergraduates who are interested in this possibility. It will be an informal session with the opportunity to ask questions.
1st February
Prof. Paul Lambert, Sociology, Social Policy & Criminology, University of Stirling Social science and social stratification: Research themes and challenges
In this session I will discuss selected themes that currently occupy a prominent position in one important area of social science research. A brief overview of the 'Social Surveys and Social Statistics' research group in the Faculty of Social Sciences will first be given. Much, though not all, of the work in that group addresses the analysis of structured empirical data about enduring systems of social inequality (or 'social stratification'). It will be argued that four methodological issues in that domain are especially important in shaping current research endeavours and opportunities. Two are about exploiting data - how social scientists confront complex categorical data; and how they make use of data on social connections. Two more are traditionally associated with analytical methods - how we approach the analysis of causal relationships; and how we appropriately convey uncertainty. Taken together, these issues influence current research agendas within 'quantitative social science' on social stratification, but they also have interesting potential for outreach and impact beyond that academic niche.
13th February
Note different day!
Still 3pm, 4B96
Jussi Korpela, University of Helsinki, Finland Focusing waves in unknown media in energy norm

We study the wave equation on a bounded domain R^m or on a compact Riemannian manifold with boundary.
Let us assume that we do not know the coefficients of the wave equation but are only given the hyperbolic Neumann-to-Dirichlet map that corresponds to physical measurements on a part of the boundary. We show that it is possible to construct a sequence of Neumann boundary values so that at a time t_0 the corresponding waves converge to zero while the time derivative of the waves converge to a delta distribution. A key feature of this result is that it does not require knowledge of the coefficients in the wave equation, that is, of the material parameters inside the media. However, we assume that the point where the energy of wave focuses is known in travel time coordinates, and satisfies a certain geometrical condition.
22nd February
Mid Semester break No seminar
27th February
Note: different day
and venue
Room 2B48
Daniel Otero, Department of Mathematics, Xavier University, USA Transforming instruction in undergraduate Mathematics via primary historical sources

The speaker is one of a team of seven mathematicians and mathematics educators, representing different universities across the United States, who have been at work to design, author, classroom test, revise, evaluate, and disseminate classroom modules called Primary Source Projects (PSPs), which are meant to teach standard topics from across the early years of the undergraduate mathematics curriculum through primary historical source materials. This endeavor, called by the acronym TRIUMPHS, intends for PSPs to replace traditional textbook presentations of mathematical content by focusing student attention on the interpretation of historical source texts combined with brief contextual material and carefully crafted exercises meant to encourage sense-making by students. PSPs are also designed to incorporate principles of active learning, wherein the bulk of classroom time is given over to student work on project tasks and exercises, both alone and in discussion with small groups of classmates, or involving the entire class, rather than to traditional lectures by the instructor.

The TRIUMPHS team, supported with funding from the US National Science Foundation, have created some 48 such modules together with a few external authors. These are now freely available from the TRIUMPHS website. Some PSPs can take as little as 30 minutes to implement, while others are designed to take up to four weeks (with median implementation time of about one week) of classroom time. There are modules written to support standard coursework from precalculus and calculus, linear algebra, differential equations, algebra, theory of numbers, geometry, analysis, statistics, and a few other subjects as well.

This talk will discuss the TRIUMPHS endeavor generally but will show examples of PSPs at work through a pair of projects authored by the speaker, one of which is an introduction to the study of trigonometry, the other of which teaches the matrix determinant.
Speaker Bio: Daniel E. Otero is Associate Professor of mathematics at Xavier University in Cincinnati, OH. His chief interests are in the history of mathematics and its uses in teaching, especially via primary sources. He is the most recent former Chair of HOM SIGMAA (the History of Mathematics Special Interest Group of the Mathematical Association of America) and was President of the Ohio Section of the MAA (2015-2016). He is currently a Visiting Fellow in the History of Mathematics at the University of St. Andrews.
8th March
Note: different venue
Room 2B129
13th March
Note different day!
Still 3pm, 4B96
David Li, Strathclyde Institute of Pharmacy and Biomedical Sciences, University of Strathclyde
15th March
Armando Marino, BES, University of Stirling
22nd March
Paul McMenemy, CSM, University of Stirling
29th March
Yulia Timofeeva, University of Warwick
5th April
Ian Gent, School of Computer Science, University of St Andrews The winnability of Klondike and many other single-player card games

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.
12th April
Prof Lei Tang
19th April
Good Friday holiday - university closed
26th April
Dr. Marc Roper, University of Strathclyde
3rd May
Sarah Thomson, CSM, University of Stirling
10th May
Stewart Blakeway, School of Computer Science, University of Manchester
Previous Seminar Series
2018:   Spring   Autumn
2017:   Spring   Autumn
2016:   Spring   Autumn
2015:   Spring   Autumn
2014:   Spring   Autumn 2013:   Spring   Autumn
2012:   Spring   Autumn 2011:   Spring   Autumn 2010:   Spring   Autumn
2009:   Spring   Autumn 2008:   Spring   Autumn 2007:   Spring   Autumn
2006:   Spring   Autumn 2005:   Spring   Autumn 2004:   Spring   Autumn
2003:   Spring   Autumn 2002:   Spring   Autumn 2001:   Spring   Autumn
2000:   Spring   Autumn 1999:   Spring   Autumn 1998:   Spring   Autumn
1997:   Spring   Autumn 1996:   Autumn  

Top image: Glazed building facades along the trade-off of operational energy consumption for heating, lighting and cooling, vs capital construction cost, with a heatmap showing the result of mining a fitness model to identify ideal glazing locations.
Courtesy of Dr. Alexander Brownlee. Related to a recent publication:

Brownlee, A. E. I. Mining Markov Network Surrogates for Value Added Optimisation. Surrogate Assisted Evolutionary Optimisation (SAEOpt) Workshop in: Companion Proc. of the Genetic and Evolutionary Computation COnference 2016, Denver, CO, USA. DOI:10.1145/2908961.2931711

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