Dr Lighton Phiri has taken up a one-year Visiting Researcher position in Road and Railway Engineering at Beijing University of Civil Engineering and Architecture (BUCEA), under the National Key Research and Development Program of China project AI-Driven Road Resilience Enhancement Technology.

On October 27, 2026, he delivered an invited talk at BUCEA on the DataLab Research Group's artificial intelligence work, centred on the pothole-detection research carried out in the Road Safety in Zambia project. The visit followed his participation in the BAAI Global AI Compute Faculty Development Initiative from October 12 to 23, 2026.

The talk

The talk, From Dashcam to Map: Applied Machine Intelligence for Road Condition Monitoring in Zambia, introduced the DataLab Research Group and its AI projects in health, governance, education and transport, then walked through how a pothole detector is built in five steps: collecting dashcam video, labelling potholes, training a YOLO object-detection model, evaluating it and deploying it. Dr Phiri demonstrated the group's mapping application, which turns ordinary dashcam video into a map of detected potholes for road agencies, and discussed lessons learned and limitations.

He closed with opportunities for AI-driven road resilience at BUCEA: moving from detecting potholes to measuring their size and severity, combining detections with traffic and pavement data to prioritise repairs, detecting other forms of road distress, monitoring roads over time, and transferring models between Chinese and Zambian roads. He proposed collaboration through shared, annotated road-distress datasets from Beijing and Lusaka, joint student projects and co-supervision between BUCEA and the University of Zambia, joint publications, and open tools that road agencies can adopt.