I am currently a Research Assistant Professor at KAIST (Korea Advanced Institute of Science and Technology). I obtained my PhD in Transportation Engineering at the University of Seoul, South Korea. Besides, I hold a bachelors degree in Statistics with Mathematics, BSc (Hons) Statistics from the University of Ghana. During my research carreer, I gained in-depth experience in the use of tools like NLOGIT, SPSS, STATA, Gephi, Python, ArcGIS Pro, and R.

My research centers on traffic safety and crash injury severity, advanced data analytics and machine learning, urban mobility systems and public transport performance, and emerging mobility technologies, including autonomous systems and electric vehicles, to support safer and more sustainable transportation systems. Here is my CV.

My research is interdisciplinary in nature. I use heterogeneity-aware models, pattern discovery techniques, and spatiotemporal analyses to uncover high-risk crash mechanisms and explain injury severity outcomes, with particular attention to vulnerable road users. Advanced data analytics and AI form the methodological core of my work, enabling the study of human–automation interaction risks, safety implications of EVs, AVs, and micromobility, and behavioral adoption under uncertainty. I also apply these methods to integrated public transport, shared mobility, and station-area environments to evaluate system performance, safety differentials, and the role of urban design. Overall, my research aims to generate data-driven insights that support safer, more efficient, and more equitable multimodal urban transportation systems.

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