Welcome to the Computing Science Seminars. Unless otherwise stated, seminars will take place in Room 4108, Cottrell Building from 15.00 to 16.00 on Friday afternoons during semester time.
Date | Presenter | Title/Abstract |
---|---|---|
Friday 13 Sep |
Dr Giancarlo
Bigi Assistant Professor Computer Science Department University of Pisa, Italy |
Computing equilibria via optimization:
In scientific contexts the term "equilibrium" has been
widely used at least in physics, chemistry, engineering
and economics within different frameworks, relying on
different mathematical models. For instance, it may refer
to physical or mechanical structures, chemical processes,
the distribution of traffic over computer and
telecommunication networks or over public roads,
production competition, the economical dynamics of offer
and demand. Many of these models (variational inequalities and non-cooperative games among others) share an underlying common structure which allows to conveniently formulate them in a unique format, the so-called abstract equilibrium problem. In this talk I will introduce it through some of the above examples and I will show how mathematical optimization can be exploited to devise algorithms for solving it. |
Friday 20 Sep |
Prof
Terry Young Professor of Healthcare Systems Information Systems and Computing Brunel University |
How can academics help to generate a
new health sector in the economy? This talk will set
out a vision of building a new Health Sector in the
Economy given the increases in health spending here in the
UK and abroad. We will describe the health challenges
posed to providers and users that we can expect over the
coming years, and how academics can respond to these
needs. We will offer a particular focus on the role
of health information in this rapidly changing
environment. Note: Prof. Terry Young is keen to bridge between disciplines, cultures and organisations using his experience of over 12 years in academia and 16˝ years in industry. Since 2001, he has built a portfolio of multi-university collaborative research in healthcare products and services. |
Friday 27 Sep |
Dr Sandy
Brownlee Senior Research Assistant Computing Science and Mathematics University of Stirling |
Fitness modelling for better
optimisation and decision making: Fitness models
(a.k.a. approximations, surrogates or meta-models) have
found a number of uses in the field of meta-heuristics.
They can be used to reduce calls to costly fitness
evaluations, overcome difficulties in the search space, or
to better understand the problem and search process. In
this presentation I will give an overview of the concept
and describe a couple of example fitness models. I will
then give some results showing how fitness models can
decrease runtime on challenging real-world problems, and
how information mined from the model can be used to inform
decision making. I will conclude with some work looking at
how fitness models can help us better understand how
metaheuristics solve problems. |
Friday 4 Oct |
Prof
Dave Marples Honorary Professor Computing Science and Mathematics University of Stirling Chief Scientist ZoomInfo |
The future power grid: The
electricity distribution grid faces a number of
significant challenges. As we move towards an
electron-centric power infrastructure the increased
demands of heat pumps and electric vehicles will place
hitherto unforeseen strains on an infrastructure that was
largely designed in the middle of the last century and
certainly didn't consider the vagaries of
distributed and intermittent power sources such as solar,
wind and wave power in mind. This lecture considers the technological solution to address these challenges by means of overlaying a control network on the legacy infrastructure to co-ordinate the activities of both sinks and sources, to ensure the network remains balanced in the face of the highly variable supply and demand that will be characteristic of our future power grids. |
Friday 11 Oct |
Dr
Alexandra Birch Research Fellow School of Informatics University of Edinburgh |
Why is statistical machine translation
(SMT) such a hard problem? During the last 20 years,
machine translation has made enormous advances, largely
thanks to adapting statistical models originally proposed
for speech recognition. Today, millions of people
regularly use SMT to translate web pages and emails, and
it is also being widely adopted in industry as a
preprocessing step for professional human translators.
However, state of the art models still struggle to
overcome problems such as differences in word order,
complex morphology, and domain adaptation. In this talk I will present an analysis of the effect of these issues on machine translation performance. I will also discuss ways of measuring word order performance and use this to evaluate discriminative reordering models. Finally I will discuss the difficulties that all natural language processing models encounter when used out in the real world: having to adapt to different test domains. In particular I will mention recent work with translating the output of speech recognition systems. |
Friday 18 Oct |
Dr Neil Urquhart Lecturer within the Institute for Informatics and Digital Innovation Edinburgh Napier University |
Scheduling and routing in the real world: This talk makes the assertion that vehicle routing research has produced increasingly more powerful problem solvers, but has not increased the realism or complexity of typical problem instances. The time has come of use realistic street network data to increase the relevance and challenge of our work. A particular benefit of real world street data is the ability to support vehicle emissions modelling. Thus allowing emissions to be used as an optimisation criterion. Two on-line demonstrations are presented which demonstrate the use of GIS data obtained from Open Street Map and Google Maps. The talk will also look at some current experiences of working with industry and solving their problems. |
Friday 25 Oct |
Mid Semester Break |
Mid Semester Break |
Friday 1 Nov |
Dr
Alan Brown Director DI Solutions Ltd. |
The next generation data warehouse:
Exponential data-growth coupled with a thirst for access
to real-time data has changed the face of the traditional
Data Warehouse. This seminar will take a close look at the
evolution of the Data Warehouse in both practice and
principle and describe the technological
advancements which have resulted in the modern, dynamic,
real-time, high volume Data Warehouse we see today. The
journey from the simple batch-populated relational
database in the 80's to the Massively Parallel Processing
(MPP) distributed databases which are dimensionally
modelled, virtualized and fed by real-time data sources is
an exciting one. However, it's a difficult journey that
continues in the face of great challenges - challenges
which are yet to be addressed. |
Friday 8 Nov |
No seminar |
No Seminar |
Friday 15 Nov |
Dr Jingpeng
Li Reader Computing Science and Mathematics University of Stirling |
Evolutionary based constructive search:
theoretic and practical point of views: This talk
presents my recently-proposed search framework (namely
“evolutionary based constructive search”), and introduces
some ideas about studying the theoretical properties of
this class of algorithms by the means of Markov chain
analysis. This framework is knowledge-based as the search
is jointly driven by experts’ domain knowledge and
evolutionary mechanism. This framework is flexible as
other meta-heuristics and hyper-heuristics can be easily
incorporated into the different steps of its search. This
framework is general as the simple heuristic, the
iterative constructive heuristic, the improvement
heuristic, ruin and recreate principal, (evolutionary)
squeaky wheel optimisation, and even the (1+1)
evolutionary algorithm are all its special cases. |
Friday 22 Nov |
Dr
Wendy Moncur Reader in Sociodigital Interaction School of Computing University of Dundee |
Providing adaptive health updates across
the personal social network: The arrival of a new
baby is usually an exciting event for parents. However, if
the baby is very unwell and needs to receive medical
attention, it is also a worrying time. Family and friends
are likely to be concerned too, and want updates about the
health of the baby and the wellbeing of the parents. We investigated what information parents were willing to share, and how they adapted this information to individual members of their personal social network. Fieldwork was conducted with parents whose sick, newborn babies were being cared for in a Neonatal Unit (NNU) in a large hospital. We found that parents adapted the information they shared based on how close they were emotionally to members of their network, and to each network member’s tendency to worry and empathize. Using this understanding, we developed a prototype software tool, which created messages containing summaries of large volumes of complex medical data about the baby, plus information about the parents and the hospital. The tool automatically adapted these messages to individual members of parents’ social networks. We believe that these findings can be generalized to the automatic adaptation of information content across the social network in other sensitive contexts, notably when users are chronically or critically ill. (link to article) |
Friday 29 Nov 2:00 PM |
Prof
Mark Harman Professor of Software Engineering CREST Department of Computer Science University College London |
Search Based Software Engineering: This talk will explain some of the many exciting challenges that software engineering poses to the evolutionary computation and optimisation community. Software is virtual and inherently adaptive, making it better suited to evolutionary computation and optimisation than any other engineering material. As we shall see in this talk, this is leading to breakthroughs at the interface of software engineering and evolutionary computation. The talk will survey existing results in the area of research known as Search Based Software Engineering (SBSE) as well as recent developments in SBSE and Dynamic Adaptive SBSE, focussing on work at the interface of software engineering and evolutionary computation. |
Previous Seminar Series |
---|
2013: Spring |
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 |
Top image:
Local Optima Network of a Combinatorial Fitness Landscape.
Nodes represent local optima and edges indicate that there are
transitions between their attraction basins following a sequence
of single mutation operations. Colors represent fitness values
with red being high and blue low. Courtesy of Dr. Sebastien Verel,
joint work summarised in:
G. Ochoa, S. Verel, F. Daolio and M. Tomassini (2013) Local Optima Networks: A New Model of Combinatorial Fitness Landscapes, Recent Advances in Fitness Landscapes. A. Engelbecht and H. Richter (Eds.), Springer.
Last Updated: 11 November 2013.