Dr Nick Malleson
- Position: Professor
- Areas of expertise: agent-based modelling; geographical information science; crime modelling; city simulation.
- Email: N.S.Malleson@leeds.ac.uk
- Phone: +44(0)113 343 5248
- Location: 10.114 Irene Manton Building
- Website: Personal Research Website | Twitter | ORCID
Profile
Main research interests: quantitative spatial analysis, geography of crime, agent-based modelling, social-media data.
Dr Malleson is a Professor of Spatial Science and a member of the Centre for Spatial Analysis and Policy (CSAP). His primary research interest is in developing spatial computer models of social phenomena with a particular focus on crime simulation and models of urban areas.
For the latest research updates see:
- My personal research website
- The surf project
- The dust project.
- The Multi Agent Systems and Simulation (MASS) research group
Employment history
- July 2012 – present. Lecturer & Associate Professor in GISc, University of Leeds.
- Feb 2010 – July 2012. Research fellow, University of Leeds.
- Oct 2006 – Feb 2010. ESRC-funded doctoral student with lecturing duties, University of Leeds. Sept 2005 – Aug 2006. Masters student, University of Leeds.
- Sept 2002 – Aug 2005. Undergraduate student, University of Leeds.
Major Grants & Prizes
- Royal Geography Society (RGS) Gill Memorial Award for outstanding early career research in agent-based social geography [geocomputation]. (Further details).
- €1.5M (£1.3M) ERC Starting Grant entitled Data Assimilation for Agent-Based Models (dust.leeds.ac.uk/).
- £312k ESRC Future Research Leaders grant entitled Understanding Urban Movements through Big Data and Social Simulation (surf.leeds.ac.uk/).
Research interests
Data Assimilation for Agent-Based Modelling (dust)
This 5-year research project, which is being funded by the European Research Council, will develop dynamic data assimilation methods for use in agent-based modelss.
surf - Simulating Urban Flows
The aim of the surf project is to create a simulation that is capable of modelling the individual movements of people in an urban environment as they undertake their daily routine activities (commuting, shopping, schooling, etc.). It will use a combination of 'big data' analysis and cutting-edge computer simulation to create a highly realistic siulation that we can use to better undestand the daily ebb and flow of urban life. Ultimately, the results will be used to quantify the impacts of levels of crime and pollution on citizens
Consumer Data Research Centre (CDRC)
The aim of the CDRC is to create, supply, maintain and deliver consumer-related data to a range of end users, alongside a programme of research and outreach activities. I am leading a research strand that will apply advanced spatial analysis and modelling techniques to reveal new insights into the causes and distributions of crime through the inclusion of novel ‘Big’ data sources.
N8 Policing Research Partnership: Innovation and the Application of Knowledge for More Effective Policing
This 5 year project will develop and test mechanisms of research co-production between the Police and Universities. I am involved in the Policing Data Analytics strand, that will look at new ways to safely access and analyse police and crime data.
GeoCrimeData: Exploring Geospatial Data for Crime Analysis
The work of crime analysts and modellers could benefit substantially from the use of new spatial data sets that are becoming more readily available. Examples include road networks (e.g. Open Street Map), building boundary datasets (e.g Ordnance Survey MasterMap) as well as under-utilised social network data (e.g. Twitter) or other volunteered sources. The GeoCrimeData Project is exploring many novel data sources and manipulating them using geographical routines in order to generate new forms of spatial intelligence that can help to add value to the interpretation of recorded crime data
Agent-Based Modelling of Crime
Crime is an extremely complex phenomenon which is driven by a wide array of both environmental and human-behavioural characteristics. Traditional techniques which utilise statistical methods to investigate crime and predict future crime rates struggle to incorporate the highly detailed, low-level factors which will determine whether or not a crime is likely to occur.
This research utilises agent-based modelling which is a methodology that can account for these low-level characteristics. By incorporating detailed behavioural information into a simulation consisting of many 'intelligent' agents it might be possible to produce hypotheses regarding how offenders behave in the real world and the factors which determine their movements.
The product of the work will be an application which could be used by local authorities to predict the effects of new environmental developments or policies. Specifically, the model will be used to experiment with the effects that a major development project will have on rates of residential burglary in Leeds.
<h4>Research projects</h4> <p>Any research projects I'm currently working on will be listed below. Our list of all <a href="https://environment.leeds.ac.uk/dir/research-projects">research projects</a> allows you to view and search the full list of projects in the faculty.</p>Qualifications
- PhD, School of Geography, University of Leeds
- MSc, Multidisciplinary Informatics, University of Leeds
- BSc, Computer Science, University of Leeds
Research groups and institutes
- Institute for Spatial Data Science