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DSA Research Award

Data Science Africa announced a call to support research addressing local challenges in Africa in August 2020. The aim was to support up to ten pilot and early stage research projects that leverage data science, artificial intelligence (AI) and machine learning (ML) methods to develop tools with broad societal benefits. We are happy to announce the projects selected.


  • Early detection and diagnosis of crop diseases in asymptomatic plants: acquisition and machine learning analysis of spectral data.

    PI: Dr. Godliver Owomugisha, Makerere University, Uganda

  • Rice Plant Disease Detection and Diagnosis using Deep Convolutional Neural Networks and Hyperspectral Imaging.

    PI: Prof. Mohamed A. ElHelw, Nile University, Egypt

  • Combining Data science and Remote Sensing for Highland Wheat Yield Prediction Under Resource limited Ethiopian Agricultural Set-up.

    PI: Mr. Andualem Aklilu, Ethiopian Space Science and Technology Institute, Addis Ababa University, Ethiopia

  • Development of rapid assay for the on-site detection of capripoxvirus.

    PI: Mr. Bramwel Waswa Wanjala, Kenya Agricultural and Livestock Research Organization (Biotechnology Research Institute), Kenya

  • An informal road detection neural network for societal impact in developing countries.

    PI: Dr. Inger Fabris-Rotelli, Department of Statistics, University of Pretoria, South Africa

  • Understanding Fruit Bat Movement Pattern Leveraging on Radio Telemetry and Data Analytics .

    PI: Dr. Segun Adebayo, Bowen University, Nigeria

  • Contribution of Internet-of-Things, Machine Learning and Remote Sensing for improving groundwater assessment in a semi-arid region (north-eastern Benin) .

    PI: Mr. Houégnon Géraud Vinel Gbewezoun, Laboratoire d’Hydrologie Appliquée (LHA), Université d’Abomey-Calavi (UAC), Benin Republic

  • Overcoming Open Learning Recession using Analytics and Machine Learning .

    PI: Dr. Khamisi Kalegele, Open University of Tanzania, Tanzania

  • Text Mining of Social Media Luganda Data to Track Misinformation and Perceptions Related to COVID-19 Transmission Mitigation Strategies .

    PI: Dr. Joyce Nakatumba-Nabende, Makerere University, Uganda

  • Modelling the preferred route of desert locust: A neural network approach .

    PI: Dr. Dennis Mugambi Kaburu, Jomo Kenyatta University of Agriculture and Technology, Kenya