Simon Dobson

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Simon Dobson, FRSE

Prof

 https://orcid.org/0000-0001-9633-2103

  • School of Computer Science, North Haugh, St Andrews, Fife, KY16 9SS, UK

Accepting Postgraduate Research Students

PhD projects

Network science emerged as a way of applying concepts from statistical physics to a wide range of systems that can be represented as pairwise interactions. It has been extremely successful as a framework for modelling phenomena ranging from crystal formation to epidemic spreading.

However, it is now clear that this approach has some severe limitations. Firstly, not all interactions are pairwise: many occur only when a larger group of components are brought together, for example in social interactions, animal flocks, robot swarms, or chemical reactions. Secondly, a process' evolution may be affected by the fine structure of the network, in terms of the exact details of how neighbourhoods are formed. Thirdly, both these phenomena may vary in time and space, so that the process' evolution itself evolves and self-organises alongside the evolution of the underlying network and its higher-order features.

All these phenomena have been studied individually, using network tools such as simplicial complexes or hypergraphs combined with analysis techniques based on (discrete) sheaves and differential geometry. We are however still seeking a thorough treatment, both mathematically (to model the interactions analytically) and computationally (to simulate these processes accurately, efficiently, and at scale). We therefore need to extend both the theory and practice of network science to encompass higher-order interactions with significant dynamic behaviour.

I'm looking for students wanting to contribute to the study of higher-order networks, using some appropriate mixture of theory and practice: both are equally important in addressing the scientific questions of interest. This would suit someone with an interest in complex systems, network science, and simulation (in some combination). Our experimental work is conducted almost exclusively using Python, and we have a considerable investment in computational tooling, including libraries for network processes and simplicial topology that can be used as starting points for experiments. We also have several potential application areas, including in epidemic modelling and sensor networks for environmental and ecological projects, in conjunction with other groups within St Andrews.

Personal profile

Research overview

I'm a computer scientist interested in complex systems, where chains of cause and effect can be difficult to establish. I build computational tools for simulation at scale and in the cloud, integrate sensors and real-time data, and develop new methods for data analytics.

Profile Keywords

complex systems; network science; simulation; computational science; sensor networks; data analytics; data science

Biography

Simon Dobson is Professor of Computer Science in the School of Computer Science at the University of St Andrews, and was Head of School from 2007 – 2021. He was elected Fellow of the Royal Society of Edinburgh, Scotland's national academy, in 2020, and serves as a science adviser to the Scottish government as a member of the Scottish Science Advisory Council.

Simon's main home page and blog can be found at simondobson.org.

Simon works on complex and sensor systems, especially on sensor analytics and the modelling of complex processes. His research has generated over 150 internationally peer-reviewed publications, driven by leadership roles in research grants worth over EUR30M – most recently as part of a £5M EPSRC-funded programme grant in the Science of Sensor Systems Software He has served, amongst other activities, on the steering committee of the ACSOS conference; as programme and general chairs for the IEEE International Conference on Autonomic Computing; as an associate editor of ACM Transactions on Autonomous and Adaptive Systems; as a member of the executive of UKCRC, the expert committee on UK computing research; as the chair of the BCS Distinguished PhD Dissertations award panel; and on the programme committees of a wide range of leading international conferences and specialised workshops. He was a director and vice-president of the European Research Consortium for Informatics and Mathematics from 2006 – 2009, and has served on a number of national and EU committees and strategic initiatives.

Simon has previously worked at the UK STFC‘s Rutherford Appleton Laboratory; at Trinity College Dublin and UCD Dublin in Ireland; and was also the founder and CEO of Aurium, a research-led Dublin-based start-up company. He holds a BSc from the University of Newcastle upon Tyne and DPhil from the University of York, both in computer science, is a Chartered Engineer and a Fellow of the British Computer Society.

Teaching activity

At undergraduate level I teach:

As part of the new Digital MSc in Data Science I teach:

  • CS5728 Complex systems modelling and simulation

I also supervise final-year, MSci, and MSc projects.

Industrial relevance

Founder and CEO of Aurium, a start-up company spun-out to commercialise work in intelligent travel systems, 2001-2003

Academic/Professional Qualification

Chartered Engineer (CEng), 1996

Chartered Fellow (FBCS), British Computer Society, 2008

Fellow of the Royal Society of Edinburgh (FRSE), 2020

External positions

Member, Scottish Science Advisory Council

1 Mar 2025 → 29 Feb 2028

Executive, UK Computing Research Committee (UKCRC)

1 Nov 2022 → 31 Oct 2025

Expertise related to UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being
  2. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy
  3. SDG 11 - Sustainable Cities and Communities
    SDG 11 Sustainable Cities and Communities

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  • 2 Membership of research network
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  • 1 Editor of research journal
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