Racheal Claire Kyomukama

Racheal Claire Kyomukama is an MSc fellow at She Data Science (SHEDs), a collaborative research training program between the Global Health Sciences (IGHS) at the University of California San Francisco (UCSF) and the African Center of Excellence in Bioinformatics and Data Intensive Sciences, Uganda (ACE-Uganda) that aims to train and advance Ugandan women in data science. Upon completion of her undergraduate studies, she joined ACE-Uganda as an intern in the Combination Drug Investigation Group (CODING) that leverages in silico approaches to design synergistic drug combinations for bacterial and fungal infections. Her research interests lie in leveraging data science techniques to address the challenge of antimicrobial resistance (AMR). Through advanced machine learning algorithms and statistical methods, she is exploring the design of optimal antimicrobial combination therapies and analysis of diverse datasets to understand the mechanisms of resistance and factors that influence drug efficacy. This interdisciplinary approach combines computational methods with microbiological insights to contribute to more effective antimicrobial treatments and combat the problem of AMR.