As a Bioinformatics and Health Data Scientist,
my work lies at the intersection of global health and data science, driving solutions to pressing public health challenges:
"roles"
· PhD Fellow – Bioinformatics & Data Science (MakDARTA, Makerere University)
· WHO/TDR Clinical Research Leadership Fellow – ISARIC, University of Oxford
· Visiting Graduate Scholar – Institute for Global Health Sciences, University of California San Francisco IGHS-UCSF
· Scholar – Artificial Intelligence for Development (AI4D), sponsored by IDRC / UK FCDO
· Founder – CareerBiome
Current Research
My current research focuses on leveraging routine health data and AI-driven insights to improve and strengthen public health systems. I work with large-scale HIV program data to build predictive models of virological failure and long-term outcomes and to demonstrate how data-driven tools can be embedded into real-world health system workflows in Africa.
My scientific journey began at the bench. With a background in Biomedical Laboratory Technology and an MSc in Bioinformatics, I spent my early career generating data—sample collection, DNA/RNA extraction, PCR, sequencing and molecular assays for infectious diseases—and used next-generation sequencing and custom pipelines to study low-abundance HIV variants.
My work has ranged from deep sequencing of low-abundance HIV drug-resistance variants and contributing to the development of the HIVDRIVES pipeline, to predictive modelling of HIV virological failure and participation in multi-country pandemic data initiatives.
I also served on Uganda’s national rapid response team during the COVID-19 pandemic. These experiences highlighted a critical gap: I knew how to generate high-quality data, but I wanted to understand how those data could be translated into insights that shape clinical decisions and public health policy. This led me fully into bioinformatics, predictive analytics and health data science.
I have contributed to multiple research projects, applying bioinformatics tools, pipelines and big data analysis. (Here is a list of some publications via Google Scholar)
I have deepened my skills through international fellowships and placements at the University of Cambridge (Cancer Research UK-Cambridge Institute), the UCSF Institute for Global Health Sciences (Visiting Graduate Scholar and inaugural CPPR Scholar) and as a WHO/TDR Clinical Research Leadership Fellow with ISARIC at the University of Oxford.
Mentorship & Capacity Building.
I am deeply inspired by Africa’s data revolution and the potential of machine learning and AI to transform health outcomes, particularly in resource-limited settings. Beyond research, I am committed to mentoring and empowering the next generation of scientists and data professionals. I support training in computational biology, data literacy and research reproducibility, and I founded CareerBiome to create storytelling-driven mentorship and science communication that helps early-career professionals align personal growth with professional success.
Speaking & Panel Engagements.
- Speaker & Panelist – British Computing Society (BCS), British Early Career Webinar
- Speaker & Panelist – African Research Network for Neglected Tropical Diseases (ARNTD)
- Presenter & Panelist – Data for Health in Africa & DS-I Africa 5th Consortium Meeting (Accra, Ghana)
- Presenter – International Society for Computational Biology (ISCB) Africa/ASBCB (Cape Town, South Africa)
- Presenter – H3Africa Consortium Meetings (Abuja, Nigeria & Cape Town, South Africa)
- Delegate – American Society of Tropical Medicine and Hygiene (ASTMH) Meeting (Seattle, United States)
Affiliations & Volunteering.
- Support team – International Pandemic Sciences Institute Conference 2024, University of Oxford
- Makerere University – School of Biomedical Sciences / related programmes
- DS-I Africa programmes
- CareerBiome – Founder & Director
- Local and continental societies (e.g. H3Africa, AfSHG)
skills
1
Self-awareness:
- Research & cohort design.
- Data analysis (big data, R programming, machine learning, data visualisation).
- Science communication
2
Mindfulness:
- Data analysis (big data, R programming, machine learning, data visualisation).
3
Consistency:
Bioinformatics & genomics.
4
Grace:
Allowing myself to make mistakes and learn from them.
5
Balance:
Prioritizing rest and recovery alongside work and ambition.
How Data Science is Evolving in Relation to Personal
Well-being
With the rise of wearable technology & health apps, we are collecting more data than ever about our daily habits—sleep patterns, physical activity, heart rate, & even stress levels.
Biggest Influence on My Wellness Journey
My biggest influence has been my family, particularly my parents, who instilled in me the values of resilience, kindness, and self-care.
Tracking and Measuring Wellness Outcomes
I track wellness outcomes through a combination of subjective and objective measures. Journaling helps me reflect on how I’m feeling emotionally and mentally.