Tom Komar

Tom Komar is a Machine Learning Operations Engineer at Newcastle University and an interdisciplinary researcher working across urban studies, geospatial data, environmental systems, and data-informed decision support. His work examines how people, infrastructure, and services interact across cities and regions, with a particular interest in turning continuous and fragmented observations into practical evidence for planning and policy. His research has included urban mobility and footfall forecasting, CCTV-based traffic analysis, smart-city sensing infrastructure, public-space analysis using vision-language models, and the reliability of spatial and environmental data. He is particularly interested in operationalising machine-learning methods through reproducible data pipelines and connecting technical analysis with real-world decision-making. His work aims to support more informed, responsive, and resilient approaches to managing urban and transport systems.

Within DARe, Tom is focussing on operationalising data and machine-learning workflows that support integrated transport modelling and resilience analysis. His work explores reproducible processing of urban sensing and mobility data, model orchestration and forecasting, and tools that connect complex datasets with modelling frameworks and decision-support outputs.