I'm thrilled to share a significant milestone in my academic journey – successfully defending my PhD dissertation. The heart of my research has revolved around a critical global issue — road accidents, claiming 1.25 million lives annually and ranking as the eighth leading cause of death worldwide according to the World Health Organisation. My PhD dissertation aimed to unravel the complexities surrounding road accident risk, delving into the uncharted territory of machine learning in this domain.

My research revolved around the creation of a novel modular data mining framework for road accident analysis. This framework was designed to streamline the intricate process of road accident data preparation and offer greater interpretability for machine learning model outputs. It empowered researchers to comprehensively assess road accident risks by processing raw accident, vehicle, road, and victim data, ultimately leading to safer road designs and more effective countermeasures.

To demonstrate the practicality of this framework, I implemented a concept demonstrator as a Python-based solution. Real-world road accident data from Greater Manchester, UK, became the canvas for testing each component of the framework. The results were compelling, reaffirming the potential for adopting innovative approaches in road safety research.

After almost a year of delay brought about by the COVID pandemic, finally walking across the stage at my graduation ceremony was a moment of profound accomplishment and gratitude. The support of my family and friends, the camaraderie of my fellow researchers, and the invaluable lessons learned along the way have been instrumental in this achievement. The road may have been long, but the destination was more than worth it.