Workshop 2026- Rwanda
Organisers
- HISP Centre at University of Oslo (HISP UiO)
- Ministry of Health, Rwanda
- HISP Rwanda
- CSID Network
- Data Lab for Social Good Research Group, Cardiff University, UK.
- TRUST - The Norwegian Centre for Trustworthy AI
Organising committee
- Kristin Braa (HISP UiO)
- Muhammed Semakula (MoH Rwanda)
- Jean Paul Hategekimana (HISP Rwanda)
- Bahman Rostami-Tabar (Cardiff University)
- Angela Okune (CSIDnet)
- Geir Kjetil Sandve (TRUST AI Centre)
Instructors and mentors
- Muhammed Semakula (MoH Rwanda)
- Georges Bucyibaruta (UGHE)
- Geir Kjetil Sandve (TRUST AI Centre)
- Bahman Rostami-Tabar (Cardiff University)
- Harsha Halgamuwe Hewage (Cardiff University)
- Knut Rand (TRUST AI Centre)
- Halvard Emil Sand-Larsen (TRUST AI Centre)
- Herman Tretteteig (HISP UiO)
Learning aims
Understand the full picture of spatiotemporal modelling for an operational context - the role of data, models and evaluation for an early warning system.
Understand how climate-sensitive disease forecasting can be approached through modelling.
Develop an understanding of the statistical underpinnings of various modelling approaches, as well as what different evaluation metrics and visualisations capture mathematically.
Establish an effective software setup for the development and use of spatiotemporal models using the open-source Chap modeling platform and DHIS2 modeling app - a setup including version control and sharing of developed code, streamlined installation of libraries, streamlined running of developed code, and good organisation of code and data.
Make progress on a concrete case brought to the workshop, including development or application of suited models and rigorous evaluation of how this initial model performs.
Materials
Excercise and data materials for the workshop are available here.