Nick Malleson

Professor, University of Leeds and Turing Fellow

Dr Malleson is Professor of Spatial Science at the Centre for Spatial Analysis and Policy at the School of Geography, University of Leeds, UK. He has a PhD in Geography and undergraduate degrees in Computer Science (BSc) and Multidiciplinary Informatics (MSc). Most of his research focuses on the development of computer models that can help to understand social phenomena. He has particular interests in simulations of crime patterns, and in models that can be used to describe the flows of people around cities. More recently, he has become in interested in how ‘big data’, agent-based modelling, and smart cities initiatives can be used to reduce the impacts of problems like pollution or crime.

The aim of this project is to develop methods that can be used to better understand uncertainty in individual-level models. In particular, it will explore and extend the state-of-the-art in two related areas: ensemble modelling and emulators for use in individual-level models. Ensembles are groups of models that are initialised with slight variations in their starting conditions (either in parameter values or input data) and then executed simultaneously. The distributions of outputs from ensembles are indicative of the range of possible outcomes that a simulation might produce, and the uncertainty associated with particular outcomes.

Although widely used in the physical sciences, the use of ensembles in individual-level modelling (beyond simple parameter sweeps) is limited. An improved understanding about how ensembles can be applied, how their outputs can be interpreted, and how they can inform our understanding of where uncertainty arises, in the context of agent-based modelling, will be extremely timely and valuable. The project will also investigate emulators, and their applicability to individual-level models.

The motivation behind the use of emulators is that individual-based simulations are usually extremely computationally expensive. An emulator is a simple model that mimics the behaviour of a more complex model. A good emulator could be used in an ensemble, for example, where the overall aim is to explore the distribution of model outcomes, not analyse the results of a particular model configuration in detail. The project will, therefore, explore the use of emulators as a means of simulating the behaviour of more complex agent-based models.

Dr Malleson was recently awarded the Gill Memorial Award For outstanding early career research in agent-based social geography from the Royal Geographical Society. He has also recently secured €1.5M from the European Research Council (Starting Grant) for a project to explore the use of data assimilation methods in agent-based urban models.



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