معرفی
Roger Beecham is Associate Professor in Visual Data Science at the School of Geography, University of Leeds, and Director of Research & Innovation at the Leeds Institute for Data Analytics (LIDA). He co-leads LIDA's Visualization and Science of Data Science programmes and serves as Programme Leader for GISc Distance Learning. His academic home resides within the Faculty of Environment, where he bridges geographical analysis with cutting-edge data science methodologies.
His research spans Data Visualization, Spatial Statistics, and Applied Data Science across transport, health, crime science, and political geography domains. Beecham develops visualization techniques for analyzing large social science datasets, with particular focus on uncertainty quantification and methodological rigor. His work addresses the 'Forking Paths' problem in data analysis and promotes transparent scientific practices through visual analytics. Current projects include INFUZE (zero-carbon mobility) and SaferActive, funded by EPSRC, ESRC, ERC, NIHR, and Wellcome Trust.
Beecham's scholarly contributions manifest in top-tier journals like IEEE TVCG, Accident Analysis & Prevention, and Transport Research Part C. His upcoming 2025 CRC Press book Visualization for Social Data Science synthesizes his methodological innovations. Research outputs demonstrate consistent focus on visual inference frameworks, spatial pattern analysis, and open-source implementation.
- EPSRC-funded transport safety research
- Alan Turing Institute Methods Challenge leadership
- Wellcome Trust health geography projects
- ERC spatial data science collaborations
He supervises doctoral researchers including Juan P. Fonseca-Zamora, Juliana Novaes, and Seán Ó Héir through the SENSE CDT program. Teaching responsibilities include GEOG5009 Visualization for Social Data Science and GISc Distance Learning MSc coordination. Beecham maintains active GitHub repositories demonstrating reproducible research practices and collaborates extensively through the Institute for Spatial Data Science.
