Draft:Mirugwe Alex

Alex Mirugwe is a Ugandan data scientist, researcher, and academic whose work applies machine learning and artificial intelligence to public health problems in sub-Saharan Africa.[1] Since 2022 he has worked as a data scientist with the Monitoring & Evaluation Technical Support (METS) program at Makerere University School of Public Health, a project supported by the United States Centers for Disease Control and Prevention (CDC), where his research has contributed to systems for HIV patient retention, tuberculosis and cervical cancer screening, and epidemic outbreak monitoring in Uganda.[1] He has authored or co-authored more than ten peer-reviewed journal articles on artificial intelligence in healthcare and public health informatics.[1]

Education

Mirugwe studied computer engineering at Makerere University in Kampala, Uganda, graduating with a Bachelor of Science in 2019 after completing a dissertation on a low-cost wireless television audio transceiver.[1] He subsequently enrolled at the University of Cape Town in South Africa, where he completed a Master of Science in Data Science in 2021. His master's thesis, supervised by Juwa Nyirenda and Emmanuel Dufourq, examined the automated detection of bird species from webcam-captured images using deep learning, and was later presented at the 43rd Annual Conference of the South African Institute of Computer Scientists and Information Technologists.[1][2]

Career

Public health data science

Mirugwe joined the Makerere University School of Public Health in March 2022 as a data scientist attached to its CDC-funded Monitoring & Evaluation Technical Support program. In this role he has worked on machine learning systems intended to support Uganda's national HIV response, including a model that flags patients at elevated risk of disengaging from care or failing to achieve viral suppression, work that has been credited with measurable reductions in patient attrition at pilot facilities.[1] He also developed a deep learning system for tuberculosis and cervical cancer screening that was piloted across eleven health facilities in Uganda, and a probabilistic record-linkage algorithm used to identify and remove duplicate HIV patient records across facilities supported by the U.S. President's Emergency Plan for AIDS Relief (PEPFAR).[1] During the 2022 Ebola outbreak in Uganda, he conducted a sentiment analysis of more than 20,000 social media posts to help inform the government's public health risk communication strategy, work that was later published in the journal Life.[1][3] He has additionally built a retrieval-augmented generation chatbot, based on a fine-tuned LLaMA language model, that allows public health staff without technical training to query HIV surveillance databases using natural language.[1]

Academic teaching

Alongside his research work, Mirugwe held an academic post as an assistant lecturer in the Faculty of Science at Victoria University in Kampala between January 2022 and February 2024, where he taught courses on Python programming, machine learning, deep learning, and artificial intelligence at both undergraduate and postgraduate level, and contributed to the design of the university's BSc in Software Engineering and MSc in Blockchain Technology curricula.[1] Earlier in his career, while completing his master's degree, he worked as a tutor in the Department of Computer Science at the University of Cape Town from January to September 2021, supervising undergraduate laboratory sessions on regression, decision trees, and support vector machines.[1]

Research and publications

Mirugwe's published research spans machine learning applications in HIV care, medical imaging, agricultural quality control, and epidemic response. His work on patient deduplication in Uganda's electronic medical records system was published in BMC Digital Health,[4] while his research on predicting missed HIV clinic appointments using transformer-based models appeared in BMC Medical Informatics and Decision Making.[5] A comparative study of convolutional neural network architectures for tuberculosis detection in chest X-rays was published in JMIRx Med in 2025,[6] and his work on federated learning for resource-constrained healthcare systems appeared in Medinformatics.[7] He has also published on artificial intelligence applications outside healthcare, including a multiclass deep learning model for detecting aflatoxin-related defects in Ugandan groundnuts, published in Discover Artificial Intelligence.[8] A full list of his publications is maintained on his Google Scholar and ResearchGate profiles.[9]

Commentary and public writing

In addition to his peer-reviewed output, Mirugwe writes commentary on artificial intelligence policy and evidence standards, including pieces questioning the adequacy of benchmark-based evaluation for clinical AI diagnostic tools and discussing Africa's position in global AI development, published through SSRN, Nature Africa, and the Royal Statistical Society's Significance magazine, as well as a personal newsletter on Substack.[9]

See also

References

  1. ^ a b c d e f g h i j k Mirugwe, Alex. Curriculum vitae. Retrieved 2026.
  2. ^ Mirugwe, A., Nyirenda, J., Dufourq, E. "Automating bird detection based on webcam captured images using deep learning." Proceedings of the 43rd Conference of the South African Institute, vol. 85, 2022, pp. 62–76. doi:10.29007/9fr5
  3. ^ Mirugwe, A., Ashaba, C., Namale, A., et al. "Sentiment analysis of social media data on Ebola outbreak using deep learning classifiers." Life, vol. 14, p. 708, 2024. doi:10.3390/life14060708
  4. ^ Mirugwe, A., et al. "Patient deduplication in Uganda's electronic medical records system." BMC Digital Health, vol. 4, no. 37, 2026. doi:10.1186/s44247-026-00257-w
  5. ^ Mirugwe, A., Solomon, S., Fitzmaurice, A., et al. "Visit-level prediction of missed HIV appointments." BMC Medical Informatics and Decision Making, vol. 26, no. 131, 2026. doi:10.1186/s12911-026-03434-z
  6. ^ Mirugwe, A., Tamale, L., Nyirenda, J. "Improving tuberculosis detection in chest X-ray images through transfer learning and deep learning." JMIRx Med, vol. 6, e66029, 2025. doi:10.2196/66029
  7. ^ Mirugwe, A., Nyirenda, J. "Secure and efficient federated learning for predictive modeling in resource-constrained healthcare systems." Medinformatics, vol. 3, no. 2, pp. 178–184, 2026. doi:10.47852/bonviewMEDIN52027621
  8. ^ Tamale, L., Denis, S., Drake, M., Mirugwe, A., Jude T., L. "AI-powered multiclass deep learning model for detection of aflatoxin-related defects in Ugandan groundnuts." Discover Artificial Intelligence, vol. 6, no. 291, 2026. doi:10.1007/s44163-026-01027-3
  9. ^ a b Google Scholar: Alex Mirugwe; mirugwe.com

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