Our team
The people behind the work.
A small team of researchers and engineers working across data science, computer vision, and speech and language AI, based between Kampala and the Makerere Artificial Intelligence Lab.
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Mutembesa Daniel
Co-founder & COO — Data & Operations AIA research scientist, project principal investigator, and collaborations lead at the Makerere Artificial Intelligence Research Lab. Over ten years, his focus has been impactful AI applications across Africa. His PhD work in Computer Science addresses multi-objective optimization and algorithmic mechanism design in resource-constrained contexts, including large-scale datasets for crop and livestock disease-vector surveillance, multi-objective optimization strategies for deploying mobile sensors, and social-knowledge-informed credit scoring for SMEs — extending to algorithmic fairness in the design of equitable digital micro-credit and micro-insurance systems.
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Solomon Nsumba
Co-founder — Data & Vision AIA Computer Science PhD candidate and Technical Lead at the Makerere AI Health Lab, and a Software Engineer at Sunbird AI working on machine translation and language technology for Ugandan languages, and on applied AI for public health and urban sensing. He holds an MSc in Data Communications and Software Engineering and a BSc in Software Engineering, both from Makerere University, and was an exchange fellow at the University of Washington's Paul G. Allen School (2022–2023). His work includes an AI-enabled wearable camera system for detecting medication errors (with University of Washington researchers), Ocular, a smartphone-based diagnostic microscopy tool for malaria, tuberculosis, and cervical-cancer screening, and open releases including SALT-31, a machine translation benchmark for 31 Ugandan languages, Sunflower, multilingual language models for Ugandan languages, and Urban-Noise-Uganda-61K, an acoustic dataset of Kampala and Entebbe.
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Jonathan Mukiibi
Co-founder — Speech & Language AIA research scientist focused on artificial intelligence for social impact. With a background working with the United Nations Global Pulse, he has contributed to monitoring Sustainable Development Goals through speech recognition models for social listening. A member of the IEEE Signal Processing Society, he has worked on automatic speech recognition, including addressing gender bias, and currently works with the Makerere Artificial Intelligence Lab and the Mozilla Common Voice project, building inclusive, privacy-conscious open-source datasets for low-resourced languages. His research on morphological complexity in children's speech supports multilingual transfer learning for inclusive speech tools in children's education, in collaboration with Oracle Research.