AI and Deep Learning specialist currently completing an MSc in AI and Data Analytics at the University of Leeds, UK. Focused on developing and deploying deep learning solutions to address real-world challenges, particularly in healthcare. Combines over a decade of experience in digital health and open-source development with technical expertise in Python, PyTorch, and data-driven innovation. Passionate about creating scalable, impactful technologies that improve outcomes and advance equitable access in healthcare and beyond.
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Product owner for the open‑source OppiaMobile platform, leading requirements definition, roadmap prioritisation, and iterative delivery based on user needs and field feedback.
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Supported the deployment of nationally scaled mobile health applications in Ethiopia, Uganda, and Liberia, working closely with implementation teams to adapt systems to real‑world data, infrastructure, and usability constraints.
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Collaborated with monitoring, evaluation, and analytics teams, advising on data collection approaches, usage analysis, and interpretation of quantitative and qualitative field data.
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Facilitated user‑centred design workshops with WHO stakeholders for the Global Dementia Observatory, translating complex requirements into actionable technical and data‑driven design decisions.
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Led development of the ORB platform, an open repository for health‑worker training resources, shaping platform architecture and workflows to support discoverability, reuse, and impact measurement.
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Provided strategic and technical advisory support to partner organisations, helping them align content, tooling, and delivery with program objectives and user needs.
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Supported organisations in submitting, structuring, and using content data, improving data quality and consistency to enable effective training programme delivery and evaluation.
- Co-founded and directed a non-profit organization focused on applying technology to healthcare education and training at scale, conceiving and initiating the OppiaMobile learning platform as a solution to address gaps in mobile learning for healthcare workers.
- Secured UK Aid Direct funding for a multi‑year programme in Ethiopia, responsible for technical delivery, reporting, and outcome evaluation.
- Led the technical development of the OppiaMobile learning platform, overseeing architecture, implementation, and iterative improvement informed by real‑world usage.
- Managed organisational budgeting, planning, and delivery, working with NGOs and commercial partners to align technical solutions with operational constraints.
Selected modules: Machine Learning, Deep Learning, Data Mining & Text Analytics, Cloud Computing, Algorithms
- Thesis project: A Proof‑of‑Concept Framework for Comparing Machine Learning and Large Language Models in Healthcare Using Explainable AI
International Journal of Medical Informatics (Shannon, Ireland), 101, 9–14. https://pubmed.ncbi.nlm.nih.gov/28347452/
This report shares an initial blueprint to create a scalable, locally sustainable, end-to-end content distribution process that uses mobile technology to provide frontline health workers access to relevant health content.
PloS One, 8(10), e77563. https://doi.org/10.1371/journal.pone.0077563