Rate My Professor Rebecca Killick

Professor Rebecca Killick is a Professor of Statistics in the School of Mathematical Sciences at Lancaster University. She obtained her PhD in Statistics from Lancaster University in 2012 with a dissertation on novel methods for changepoint analysis, and a BSc in Mathematics with Statistics from the same institution. Her career at Lancaster has progressed from Lecturer in Mathematics and Statistics (2013-2018) to Senior Lecturer and full Professor in 2022. Killick's research focuses on developing statistical models and methods for nonstationary time series, changepoints, multiscale methods, and wavelets, applied to environmental, health, business, and oceanographic data. She is Principal Investigator on EPSRC-funded projects such as Quantum Imaging for Monitoring of Wellbeing & Disease in Communities (2021-2026), Forecasting River Levels Utilising Non-Stationarity (2016-ongoing), and Google Summer of Code 2021, and Co-Investigator on initiatives like Detecting Soil Degradation through Sensor and Machine Learning Frameworks (2023-2024).

Killick has received the European Network for Business and Industrial Statistics (ENBIS) Young Statistician of the Year Award in 2019, the first UK recipient, recognizing her contributions to statistical models addressing real-world challenges. She joined the UK Young Academy in 2023. Professionally, she serves as Co-Editor in Chief of the Journal of Statistical Software (2020-present), Associate Editor for Data Science in Science (2021-present), ROpenSci (2021-present), and others, and holds roles including Secretary of the Royal Statistical Society Statistical Computing Section, Council Member of ENBIS, and member of the RSS Data Science Task Force and National Statistical Advisory Board. Her open-source changepoint package for R, available on CRAN, has been downloaded over 100,000 times, used by over 50 companies, and cited more than 500 times. Key publications include 'Optimal detection of changepoints with a linear computational cost' (Journal of the American Statistical Association, 2012), 'An R Package for Changepoint Analysis' (Journal of Statistical Software, 2014), and 'Detection of changes in variance of oceanographic time-series using changepoint methods' (EnviroMetrics, 2010). With over 7,100 citations on Google Scholar, her work has substantial impact in statistics and interdisciplinary fields.