Project team
- Dr Isambi Sailon Mbalawata, AIMS
- Dr Oliver Ratmann, Department of Mathematics, Imperial
- Professor Samir Bhatt, School of Public Health, Imperial
- Dr Alexandra Blenkinsop, Department of Mathematics, Imperial
- Dr Juliette Unwin, University of Bristol
- Dr Elizaveta Semenova, School of Public Health, Imperial
- Prof. Blaise Tchapnda, AIMS Rwanda
Project summary
With funding awarded from the AIMS-Imperial Global Education Seed Fund, Dr Alexandra Blenkinsop (Department of Mathematics), Dr Juliette Unwin (now Lecturer at the School of Mathematics at Bristol, previously Department of Infectious Disease Epidemiology), and two PhD students from Imperial’s StatML CDT travelled to AIMS Rwanda to deliver a hands-on workshop in Modern Statistics and Machine Learning for Global Health. The workshop was developed by members of the multinational Machine Learning and Global Health network (mlgh.net), and covered topics such as modern methods in infectious disease modelling, computationally efficient non-parametric modelling, Stan, and phylogenetics.
The course is very important. In this era of AI and Machine learning, it may be the time to train more youngsters and senior researchers to explore more about the use of AI in the field of modelling and treating communicable diseases
Workshop participants came from AIMS Rwanda, and from the University of Kigali’s MSc in Malaria Modelling, and further PhD students. The prevailing feedback at the end of the course was for it to be longer, and we are pleased to develop this workshop further into an extended five-day short course to be delivered at AIMS South Africa in 2025, with additional content, longer practicals, and a larger team.
The workshop offered unique and valuable opportunities for Imperial PhD students to gain hands-on experience of developing and delivering material relevant to their own research. Following the workshop, one AIMS student continued their MSc project with remote supervision from UK-based researchers at Imperial and the Machine Learning and Global Health network, and successfully defended their thesis at the end of June.
Through this workshop, Imperial researchers and students met many researchers at AIMS, providing invaluable opportunities to engage with them, and learn about and contribute to current projects at AIMS Rwanda and the University of Kigali. The visit to AIMS Rwanda also opened up wider networking opportunities, with some of the team joining an Experts Group Workshop on Standards for Climate-Health Interactions, where they met with researchers and policymakers based in Kigali.
I have been enjoying the content and learning Modern Statistics and Machine Learning for Global Health, methodology used was really valuable, and I believe that extending the duration of the course would greatly enhance the ability to absorb and apply the knowledge effectively