Our Team

Mutembesa Daniel
Co-founder & COO - Data & Operations AI

A seasoned Research Scientist, distinguished project principal investigator, and accomplished collaborations leader at the forefront of the Makerere Artificial Intelligence Research lab. Over the 10 years, his focus lies in impactful AI applications across Africa. His current PhD in Computer Science work tackles multi-objective optimization and algorithmic mechanism design, particularly in resource-constrained contexts. Recent achievements include large-scale data sets for crop & livestock disease-vector surveillance, multi-objective optimization strategies for deploying mobile sensors. Uses social knowledge into credit scoring for SMEs. This extends to algorithmic fairness, advancing equitable design of digital micro-credit and micro-insurance systems.

Solomon Nsumba
Co-founder - Data & Vision AI

A Software Engineer and Artificial Intelligence researcher with expertise in software development, machine learning, computer vision, and practical application. Solomon holds a Master's in Data Communication and Software Engineering, and is currently pursuing a PhD in Computer Science between Makerere University and the University of Washington.

Jonathan Mukiibi
Co-founder - Speech & Language AI

A dedicated research scientist passionate about leveraging artificial intelligence to drive positive social impact. With a background in working with the UN Nations Global Pulse, he has been at the fore front of monitoring Sustainable Development Goals (SDGs) through developing Speech Recognition Models for social listening. As a member of the IEEE Signal Processing Society, He has actively contributed to the field of automatic speech recognition, particularly in addressing gender bias. Their current focus lies in the Makerere Artificial Intelligence Lab and Mozilla Common Voice Project, where he leads and volunteers on projects centered around creating inclusive and privacy-conscious open-source datasets for low-resourced languages. His breakthrough on understanding morphological complexity in children's speech aims to facilitate multilingual transfer learning for building inclusive speech tools in children's education in collaboration with Oracle Research.