Insights, updates, and stories from the ACE Uganda team
Researchers demonstrated cutting-edge work that is helping answer critical questions about infectious disease outbreaks from understanding how Ebola treatments could work across different virus strains to predicting future outbreaks before they occur.
During the visit, the delegation toured ACE-Uganda's facilities, including the High-Performance Computing (HPC) cluster, the VR Lab, and the Telelearning Facility. They also held discussions with the ACE team to learn more about the Center's training programmes, research projects, and the broader bioinformatics ecosystem in Uganda.
Over two days, researchers, policymakers, students, and global health leaders from over 17 institutions and 10 countries, gathered to explore one of the most urgent questions in modern medicine: How can AI help us stay ahead of the growing threat of antimicrobial resistance?
Just a few months ago, they were sitting among the participants, learning the foundations of data science and bioinformatics. This week, they stood confidently at the front of the room, teaching others.
When breakthroughs are made, the spotlight often shines on the scientists behind the discoveries. Yet behind every genomic analysis, disease model, and large-scale dataset is another group of experts whose work makes that science possible; high-performance computing (HPC) systems administrators.
For many young women, the dream of becoming a scientist doesn't end because of a lack of talent; it ends because no one showed them they belonged.
For many young scientists across East Africa, access to cutting-edge artificial intelligence tools has often been out of reach. That is set to change.
But for Africa, there's a challenge: many of the genetic tools used to predict disease risk have been built using data from European populations, making them far less accurate for African communities.
What if a process that once took scientists months or even years; could be completed in a matter of minutes?
Every day, researchers generate vast amounts of health data; from genomic sequences and disease surveillance records to artificial intelligence models. Turning that data into life-saving discoveries, however, requires one critical ingredient: computing power.
