Explainable Ensemble Learning and Trustworthy Open AI for Customer Engagement Prediction in Retail Banking. - Sudi Murindanyi; Margaret Nagwovuma; Barbara Nansamba; Ggaliwango Marvin (IC3, 2023)

Explainable Machine Learning Models for Swahili News Classification. - Sudi Murindanyi; Brian Afedra Yiiki; Andrew Katumba; Joyce Nakatumba-Nabende (NLPIR, 2023)

Machine Learning Analysis of Radio Data to Uncover Community Perceptions on the Ebola Outbreak in Uganda. - Joyce Nakatumba-Nabende; Jonathan Mukiibi; Tobius Saul Bateesa; Sudi Murindanyi; Andrew Katumba; Chodrine Mutebi (ACM J. Comput. Sustain. Soc., 2024)

Luganda Speech Intent Recognition for IoT Applications. - Andrew Katumba; Sudi Murindanyi; John Trevor Kasule; Elvis Mugume (CoRR, 2024)

Enhanced Infield Agriculture with Interpretable Machine Learning Approaches for Crop Classification. - Sudi Murindanyi; Joyce Nakatumba-Nabende; Rahman Sanya; Rose Nakibuule; Andrew Katumba (CoRR, 2024)

Deep learning for accurate B-line detection and localization in lung ultrasound imaging. - Nixson Okila; Andrew Katumba; Joyce Nakatumba-Nabende; Cosmas Mwikirize; Sudi Murindanyi; Jonathan Serugunda; Samuel Bugeza; Anthony Oriekot; Juliet Bossa; Eva Nabawanuka (Frontiers Artif. Intell., 2025)

Responsible Music Genre Classification Using Interpretable Model-Agnostic Visual Explainers. - Sudi Murindanyi; Kyamanywa Hamza; Sulaiman Kagumire; Ggaliwango Marvin (SN Comput. Sci., 2025)

PaliGemma-CXR: A Multi-task Multimodal Model for TB Chest X-ray Interpretation. - Denis Musinguzi; Andrew Katumba; Sudi Murindanyi (CoRR, 2025)