Lilia Potseluyko
Papers
1
Total Citations
8
H-Index
1
About
Lilia Potseluyko is a researcher at the forefront of digital infrastructure and geospatial data science, with a primary focus on developing high-fidelity datasets for transport asset management. Her most notable contribution is the creation of the **CAMHighways dataset**, a pioneering resource built from mobile mapping surveys covering over 40 km of UK highways. This dataset provides richly annotated, textured 3D meshes, segmented point clouds, and orthomosaics for critical road assets—including pavement, traffic signs, and furniture—enabling advanced machine learning applications in infrastructure inspection and maintenance. With 8 citations since its 2024 release, CAMHighways has quickly become a benchmark for researchers working on automated road condition assessment and semantic segmentation of transport environments. Potseluyko’s work bridges the gap between raw survey data and actionable engineering insights, offering a standardized, open-access foundation for developing AI-driven solutions in civil engineering. Her contributions are particularly impactful for students and professionals seeking to apply computer vision to real-world infrastructure challenges, positioning her as a key figure in the digital transformation of highway monitoring and asset management.
Research Focus
Key Achievements
Top Papers
- 1CAMHighways: The Cambridge Highways dataset8 citations · 2024