Dr. Lillian Muyama
Dr. Lillian Muyama is an Assistant Lecturer at the College of Computing and Information Sciences at Makerere University, researcher, and Co-Director of the African Health Informatics Research Institute (AFHIRI)
Her scholarly work spans digital health, artificial intelligence, machine learning, biomedical informatics, and data-driven healthcare systems, with a strong focus on strengthening healthcare delivery in low-resource settings. Dr. Muyama has contributed to interdisciplinary research exploring artificial intelligence applications in healthcare, explainable machine learning, clinical decision-support systems, and digital innovation for health systems strengthening. Her research has examined the use of computational methods to improve diagnostics, disease surveillance, and evidence-based healthcare decision-making. Through collaborations with regional and international research teams, she continues to support innovation at the intersection of computer science, medicine, and public health. As Co-Director of AFHIRI, Dr. Muyama plays a central role in advancing research capacity building, scientific mentorship, and digital health scholarship in Africa. She has supported several emerging researchers through mentorship in research methodology, scientific communication, proposal development, and interdisciplinary collaboration. Her mentorship emphasizes innovation, ethical application of artificial intelligence, and evidence translation into healthcare practice.
At the AFHIRI Doctoral Research Progress Forum, Dr. Muyama will be mentoring doctoral researchers in Artificial Intelligence, Machine Learning, biomedical informatics, and data-driven healthcare research. Her contribution strengthens the development of interdisciplinary research skills and supports the growth of future African leaders in digital health and artificial intelligence research.
Areas of Expertise and Mentorship
Artificial Intelligence in Healthcare, Biomedical Informatics, Machine Learning Applications in Health, Clinical Decision Support Systems, Explainable AI in Healthcare, Digital Health Innovation, Data Science for Health, Interdisciplinary Health Research, Research Methodology and Scientific Communication
Google Scholar: https://scholar.google.com/citations?user=Cz17X6sAAAAJ&hl=en&oi=ao