The Department of Civil & Construction Engineering at the University of Nairobi is delighted to highlight an insightful presentation recently delivered by Billy Koech, who shared his research titled “Development of a Decision Support System for the California Bearing Ratio (CBR) Test using Machine Learning.”

In his engaging session, Billy Koech showcased how the integration of machine learning can significantly enhance traditional geotechnical engineering practices. His research focuses on developing a decision support system designed to predict outcomes and optimise processes related to the California Bearing Ratio (CBR) test, a crucial procedure used to evaluate the strength of subgrade soil and materials for road construction.

By leveraging advanced machine learning models, Billy’s system aims to:

• Improve the accuracy and reliability of CBR test predictions.

• Reduce time and costs associated with extensive laboratory testing.

• Provide engineers with a user-friendly tool to support decision-making in pavement design and material assessment.

The presentation demonstrated how data-driven technologies are transforming the civil engineering landscape, offering innovative solutions to long-standing challenges in infrastructure development. Billy Koech’s research exemplifies the department’s commitment to fostering cutting-edge research and preparing students and professionals for the evolving demands of the engineering industry.

The Department of Civil & Construction Engineering congratulates Billy Koech on his outstanding work and looks forward to further advancements and practical applications stemming from his research.

For more updates on student and staff research, please visit the department’s website or follow our official communication channels.

10 July 2025