In this Future and Emerging Technologies portrait, we interview Jane Hillston, chair of Quantitative Modelling in the School of Informatics and director of the Laboratory for Foundations of Computer Science, University of Edinburgh, UK. She reveals her experiences as scientific coordinator of the FET QUANTICOL project.

Picture of Jane Hillston

The main objective of the QUANTICOL project is the development of an innovative formal design framework that provides a specification language for collective adaptive systems (CAS) and a large variety of tool-supported, scalable analysis and verification techniques. It has been applied to better manage resources in urban systems , bicycle sharing and smart electricity grids. The QUANTICOL was  a member of Fundamentals of Collective Adaptive Systems (FOCAS), a Future and Emerging Technologies Proactive Initiative funded by the European Commission under FP7.

We talked to Professor Jane Hillston,  Chair of Quantitative Modelling in the School of Informatics at the University of Edinburgh and scientific coordinator of QUANTICOL.

Jane, what are for you the greatest scientific challenges in this project and how it benefits from the FET programme?

For the QUANTICOL project we had a clear vision of what we wanted to achieve – a suite of tools to allow designers and operators to carry out quantitative analysis of systems consisting of many interacting entities, so-callled collective adaptive systems.  In these systems the behaviour at the high level, sometimes termed emergent behaviour, is made up of the behaviour of the individual entities, but on the other hand the behaviour of the individuals is also influenced by what they perceive of the behaviour of the system.   The biggest scientific challenge in representing and analyzing such systems is their scale --- if built naively, the models that capture the behaviour will be too large or too slow to analyse, which can mean that systems are deployed without important non-functional properties such as reliability, availability and performance being assessed.  Our challenge was to devise a framework that supported modelling in a style that was nevertheless amenable to efficient analysis.  The FET programme allowed us to assemble a team of experts on all aspects of the modelling pipeline --- from language designers to work on providing concise and intuitive ways for a system designer to describe the system to applied mathematicians to develop new algorithms to advance the state of the art in scalable analysis.  The FET support for fundamental research allowed us to focus on the core scientific issues with the reassurance that the FET programme understood that it is not always possible to guarantee advances on a predetermined timescale when working on such fundamental research.

What are QUANTICOL key achievements you are most proud of?

The QUANTICOL project has made a number of strong scientific advances.  For example, a novel language to help people describe and analyse collective adaptive systems, new tools for reasoning about the behaviour of these systems in time and space (spatio-temporal model checking), a variety of algorithms for reducing the size of models in order to facilitate efficient analysis and even a new result showing how to apply these algorithms to moderately-sized systems whereas previously the approximation was only believed to work for extremely large systems.  Beyond the technical achievements I am proud of the coherent team that we formed and particularly the early career researchers who have joined us in the project and are now progressing their career elsewhere.

How will QUANTICOL change the life of European citizens?

QUANTICOL develops methods that allow planners and system operators to better understand the dynamic behaviour of large systems of many interacting components.  Within the project we focused on demonstrating our techniques in smart city contexts on systems such as bike sharing systems, and bus networks.  So, for example, we showed how to make models to predict whether a potential user will be able to find a bicycle to complete her journey between specific bike stations at a particular time, or to predict how rerouting one bus service might ease congestion within the bus network as a whole. Thus the QUANTICOL framework provides a suite of techniques to study the likelihood of certain behaviours (desirable or problematic) when the system is operating.  This is important in smart city applications, where many people are using shared resources but expect at least minimal levels of service and cost-effectiveness.  However the framework we have developed is applicable to a much wider class of systems as well, ranging from disease spread to trading relations and markets. 

Has participating in the FET programme changed your vision?

Taking part in the FET programme has encouraged me broaden my perspective and take on longer-term challenges.  The FET project was larger and longer than those typically funded under the national scheme that I have access to, and I was able to assemble a cross-disciplinary team with a range of complementary skills.

What advice would you have for young researchers or students interested in a career in research?

Find something that you are passionate about.  Key ingredients of a career in research are curiosity, hard work and perseverance.  You need to be passionate about the topic to maintain these characteristics over many years.