I am interested in software engineering, data science, the internet of things, and society. My current research focuses on the use of information technologies in enhancing the living conditions of people in low-and middle-income countries. Current research activities cover transport and agriculture sectors.

Transport Sector

Road Safety Road traffic crashes and associated road traffic injuries cause the death of approximately 1.35 million people per year. More than 90% of road traffic deaths occur in low- and middle-income countries. According to the world health organization, Africa has the highest road traffic injury death rates. Accurate reporting of road crashes and their causes can help in taking appropriate and effective road safety interventions. Unfortunately, road traffic crashes are under-reported, especially in low-income countries in which around 80% of road crash deaths are not recorded. The AutoRTC-DMS (Evidence-based Road Safety: An Automatic Road Traffic Crashes Data Management System) project aims at designing and bringing to the market innovative tools and applications to record, analyze, and share road traffic crashes information in Rwanda.

On-demand public transport In a traditional public transportation system, passengers take the autobuses at a per-designated location (bus stop) and the buses cover the predefined, fixed, routes. This sometimes leads to inefficiency as some passengers may have to wait in one part of the city while buses in another part of the same city are empty or not used at their full capacity. Consequently, passengers prefer alternative solutions like taxicabs or use their private cars to save time. This increases the number of cars in circulation leading to several disadvantages including road traffic congestion, increased emission of polluting gas, and road traffic crashes/injuries. This research line explores a transportation model in which buses have neither fixed itineraries nor predefined stops: autobuses are dynamically rerouted online to meet users’ transportation needs.


Optimization of postharvest processes This research line aims at  improving the reach and quality of farmer extension by creating digital tools and operating environments, which enable remote monitoring of farmer fields and creating a feedback channel to enable rapid in-field and mobile extension support to increase farmer productivity. Additionally, this project aims to link farmers to the market by providing real time information, digitally, to farmers on input access, market prices, quality and volumes required by farmers. Buyers will also be linked to farmers, by providing buyers with farmer location, certification details, volumes, and quality available to facilitate collection logistics. The specific objectives include digitalization of farmers and their fields, production estimation based on crop performance data, automating the management of collection centers, and linking farmers to buyers and vice versa.

Automation of IoT-based agricultural applications development Model-driven development framework for agricultural application development.