Winnie is an aspiring quantitative epidemiologist with a strong foundation in mathematical sciences and a passion for advancing disease modeling and public health solutions. She holds an MSc in Mathematical Sciences with a specialization in Disease Modelling from AIMS-Ghana and is currently specializing in Data Science and Statistics (Quantitative Epidemiology) at UHasselt in Belgium. Her diverse research experience at DAVU.AI and ICRISAT-Senegal has honed her expertise in data-driven approaches to solving complex real world agricultural challenges. Motivated by a commitment to impactful research, Winnie looks forward to expanding her knowledge in disease modeling and epidemiology at CEMA, with the goal of designing innovative tools for predicting and mitigating disease outbreaks through data and technology to address pressing public health threats effectively.

Disease Modelling| Epidemiology| Machine Learning