This research uses computational photography and machine learning to monitor electricity quality through the flickering patterns of everyday lights. By analyzing images captured in cities such as Kampala and Nairobi, the work offers a low-cost method for measuring voltage instability and improving power-grid planning in underserved communities lacking reliable electricity infrastructure.

This dissertation investigates wrong-way crashes, which are 27 times more deadly than other crash types. Using GIS and statistical modeling in South Florida, the study identifies roadway design, traffic conditions, and impaired driving as key risk factors. Findings highlight lighting, wider medians, and early police intervention as life-saving prevention strategies.