Staff Profile

Roles and Responsibilities

Associate Dean (Global) - SAgE Faculty

• International Student Experience
• Virtual Exchange

Global Director - School of Mathematics, Statistics & Physics

• International Student Recruitment
• Student Mobility 
• Engagement and Partnerships

Other School Administrative duties

• Peer Mentor Co-ordinator
• Mathematics and Statistics Outreach

Esteem Indicators

• Advance HE National Teaching Fellow
• Royal Statistical Society William Guy Lecturer 2019

Memberships

• Royal Statistical Society
• The International Environmetrics Society

Research Interests

Extremes

• Bayesian Inference for Environmental Extremes - applications to rainfall, windspeed and solar flare extremes
• Extremes of Dependent Processes

Road Safety

• Statistical Modelling of Road Traffic Accidents
• Road Safety Hotspot Prediction

Statistics Education

• Technological Innovations in Statistics Education
• Research-Informed Teaching

Undergraduate Teaching (2024-2025)

MAS2906: Computational Probability and Statistics with R

MAS3092: Global Education in Mathematics and Statistics

MAS3902: Bayesian Inference

MAS3918: Topics in Statistical Modelling A

• Articles

  • Hewett NK, Fawcett L, Golightly AG, Thorpe N. Using Extreme Value Theory to evaluate the leading pedestrian interval road safety intervention. Stat 2024, 13(2), e676.
  • Koistinen VM, Haldar S, Tuomainen M, Lehtonen M, Klavus A, Draper J, Lloyd A, Beckmann M, Bal W, Ross AB, Brandt K, Fawcett L, Seal C, Hanhineva K. Metabolic changes in response to varying whole-grain wheat and rye intake. npj Science of Food 2024, 8, 8.
  • Hewett N, Golightly A, Fawcett L, Thorpe N. Bayesian inference for a spatio-temporal model of road traffic collision data. Journal of Computational Science 2024, 80, 102326.
  • Griffiths B, Fawcett L, Green AC. Bayesian Inference for Solar Flare Extremes. Space Weather 2022, 20(3), e2021SW002886.
  • Thorpe N, Fawcett L, Linsley M, Cherry B. Saving lives with safety cameras and statistical analysis. Public Sector Executive 2019, Oct/Nov 2019, 48-49.
  • Guo X, Wu L, Zou Y, Fawcett L. Comparative Analysis of Empirical Bayes and Bayesian Hierarchical Models in Hotspot Identification. Transportation Research Record 2019, 2673(7), 111-121.
  • Fawcett L. A severe forecast. Significance 2019, 16(6), 14-19.
  • Matthews JT, Newman K, Green AC, Fawcett L, Thorpe N, Kremer K. A decision support toolkit to inform road safety investment decisions. Municipal Engineer 2019, 172(1), 53-67.
  • Fawcett L. Using interactive Shiny applications to facilitate research-informed learning and teaching. Journal of Statistics Education 2018, 26(1), 2-16.
  • Fawcett L, Green AC. Bayesian posterior predictive return levels for environmental extremes. Stochastic Environmental Research and Risk Assessment 2018, 32(8), 2233-2252.
  • Fawcett L. The CASE Project: Evaluation of Case-Based Approaches to Learning and Teaching in Statistics Service Courses. Journal of Statistics Education 2017, 25(2), 79-89.
  • Fawcett L, Thorpe N, Matthews J, Kremer K. A novel Bayesian hierarchical model for road safety hotspot prediction. Accident Analysis & Prevention 2017, 99(Part A), 262-271.
  • Fawcett L, Newman K. The storm of the century! Promoting student enthusiasm for applied statistics. Teaching Statistics 2016, 39(1), 2-13.
  • Fawcett L, Walshaw D. Sea-surge and wind speed extremes: optimal estimation strategies for planners and engineers. Stochastic Environmental Research and Risk Assessment 2016, 30(2), 463-480.
  • Fawcett L, Walshaw D. Estimating the probability of simultaneous rainfall extremes within a region: a spatial approach. Journal of Applied Statistics 2014, 41(5), 959-976.
  • Fawcett L, Thorpe N. Mobile safety cameras: estimating casualty reductions and the demand for secondary healthcare. Journal of Applied Statistics 2013, 40(11), 2385-2406.
  • Thorpe N, Fawcett L. Linking road casualty and clinical data to assess the effectiveness of mobile safety enforcement cameras: a before and after study. BMJ Open 2012, 2(6), e001304.
  • Fawcett L, Walshaw D. Estimating return levels from serially dependent extremes. Environmetrics 2012, 23(3), 272-283.
  • Fawcett L, Foster WH, Youd AJ. Using computer based assessments in a large statistics service course. MSOR Connections 2008, 8(3), 43-46.
  • Fawcett L, Walshaw D. Bayesian inference for clustered extremes. Extremes 2008, 11(3), 217-233.
  • Fawcett L, Walshaw D. Improved estimation for temporally clustered extremes. Environmetrics 2007, 18(2), 173-188.
  • Fawcett L, Walshaw D. Markov chain models for extreme wind speeds. Environmetrics 2006, 17(8), 795-809.
  • Fawcett L, Walshaw D. A hierarchical model for extreme wind speeds. Journal of the Royal Statistical Society. Series C: Applied Statistics 2006, 55(5), 631-646.