School of Informatics

Stephen Gilmore

Stephen Gilmore is a Professor in the School of Informatics at The University of Edinburgh where he is the chair of Software Systems Modelling.

Stephen Gilmore

He studied Computer Science at The Queen's University of Belfast, Northern Ireland. After completing his PhD there he moved to The University of Edinburgh to take up a lectureship position. He is a member of the Laboratory for Foundations of Computer Science and the Centre for Systems Biology at Edinburgh.

His principal area of research is centred on the application of stochastic process algebras. These are concise modelling languages for quantitative analysis of systems where concurrency plays an important role. Process algebras have a wide range of application and can be used to predict the performance of computer systems, assess their scalability under increasing load, and detect flaws and insecurities in implementations.

Professor Gilmore has an interest in software systems and quantitative modelling tools, primarily through tools and frameworks for supporting Performance Evaluation Process Algebra (PEPA). In addition, he manages the Systems Biology Software Infrastructure project (SBSI) and directs the development of the Bio-PEPA modelling software.

"Is Informatics an indiscrete science?" Monday 19 November 2012, 5.15pm Lecture Theatre 1, Appleton Tower, 11 Crichton Street, EH8 9LE

and afterwards for a Reception in the Informatics Forum 10 Crichton Street, Edinburgh EH8 9AB All welcome to attend. (RSVP Marjorie Dunlop mdunlop2@inf.ed.ac.uk)

Abstract

One of the first lessons that every student of informatics learns is that computers operate with digital logic in a discrete world of bits. Starting from this view, the right way to reason about and predict the behaviour of programs is then to use discrete mathematics to prove logical properties of interest because discrete methods are precise and exact. While this approach is clearly justifiable and sensible it is also ultimately unhelpful because it does not scale to allow us to reason about larger systems with many interacting components. At these larger scales it becomes appropriate to adopt a continuous view of the discrete entities which are involved and to work instead with approximate numerical methods rather than exact ones. To go too far in this direction and abandon discrete methods altogether would be wrong because it would move too far away from the essential nature of informatics but perhaps it is worthwhile to explore more in the direction of continuous methods and see if informatics is an indiscrete science after all.

In this inaugural lecture I will tell the story of my journey along the path from the discrete world to the continuous world with PEPA, a modelling language which was invented in Edinburgh and now is used by research groups all over the world.