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.
- Product owner for the open source OppiaMobile learning platform
- Supporting implementation of nationally-scaled mobile applications for health workers in Ethiopia, Uganda and Liberia for their Covid-19 response
- Providing support and advice for user field testing, analytics and to monitoring and evaluation teams
- User Centered Design workshops for WHO for developing a Global Dementia Observatory platform
- Leading development of the ORB platform - for sharing openly licensed health worker training content
- Strategic support to mPowering's partner organisations
- Supporting ORB users and organisations in how they can submit and use the content on ORB to deliver effective training programs for frontline health workers
A not-for-profit company promoting research, innovation and development of learning through technology, focusing on primary healthcare.
- Successfully obtaining UK AID Direct funding for 3-year project in Ethiopia to train rural health workers using mobile technologies
- Technical development of OppiaMobile learning platform
- Responsible for company and project budgeting and finances
- Liaison and collaboration with NGOs and commercial organizations for partnership and project development
Advising on and managing the implementation and development of new technologies for rural health workers - part of a joint PhD programme between Alcalá, Mekelle and Maastricht Universities
Through a Voluntary Services Overseas placement, managing the implementation of elearning in a challenging environment. Advising on the development of IT infrastructure and training local staff to ensure sustainability.
Selected modules: Machine Learning, Deep Learning, Data Mining & Text Analytics, Cloud Computing, Algorithms
Int J Med Inform. 2017 May;101:9-14. doi: 10.1016/j.ijmedinf.2017.01.016. Epub 2017 Jan 24
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. doi:10.1371/journal.pone.00775