Big Data for Household Energy Insights

2017 - 2019 The Big Data for Household Energy Insights project is housed at the Energy Research Centre at the University of Cape Town. The goals of the project are to provide strategic support and leadership to convene and mobilise key stakeholders towards building big data capabilities for domestic load research, and to deliver technical data science and stewardship activities in this regard. The project has delivered South Africa’s first online datasets of Domestic Electrical Load (DEL) studies.


Data for Municipal Infrastructure Assets (Data4MIA)

2019 Data4MIA is a student internship programme that has been designed to assist local government with collecting and updating data required for successful management of water and sanitation infrastructure assets. The programme exposes students to the technology, complex systems, software tools and challenges that local government uses and encounters on a daily basis to deliver critical infrastructure and services to the people of South Africa. The programme was developed in collaboartion with the Municipal Infrastructure Support Agency and has a direct impact on data management for Water Service Authorities in rural and distressed municipalities.


Engineers Without Borders South Africa

2013 - 2019 Engineers Without Borders South Africa (EWB-SA) is a non-profit organisation established in 2013 with a mission to empower engineers to empower communities. Since its establishment, EWB-SA has been focused on delivering programmes for youth leadership and engineering education, as well as social impact projects through our national chapter network. In 2018 EWB-SA established a unique partnership with EWB-UK and EWB-USA to collaborate on expanding the Engineering for People Design Challenge to an international audience while delivering a first-of-its-kind engineering education curriculum transformation programme to South African universities.


Deep Learning for Echocardiogram Analysis

2019 The Deep Learning for Echocardiogram Analysis code base was developed and open-sourced during the 2019 Data Science for Social Good Fellowship programme. The project automates the analysis of echocardiogram images to detect normal heart functioning and is available on github.