S. van Cranenburgh

S. van Cranenburgh is a researcher at the Delft University of Technology in the College of Technology, Policy and Management, specializing in the Transport and Logistics department. Their work bridges transportation engineering, data science, and urban analytics through innovative methodologies in machine learning and spatial-temporal modeling.

Research Focus

• Transportation behavior modeling (e.g., residential location choice).
• Advanced collision risk prediction using naturalistic driving data.
• Integration of computer vision and discrete choice models.
• Psychological impacts of urban noise pollution on health.
• Proactive risk learning from large-scale driving datasets.
• Collective perception in historic urban landscapes.

Recent Work Trends

Their publications from 2025 emphasize deep learning applications in transportation safety (neural networks, contrastive learning), spatial-temporal data analysis, and social media-driven urban dynamics studies. Key themes include data-driven policy modeling and interdisciplinary approaches combining engineering, psychology, and social sciences.

Collaborative Engagement

• Active collaboration with institutions like TU Delft's 4TU.ResearchData.
• Contributions to open-access datasets and software repositories.
• Participation in academic workshops and seminars (e.g., 2025 collective perception workshop).
• Media engagement on urban mobility topics (2016 coverage in Dutch outlets).