My research focuses on developing computational methods to analyze complex biological data, with a focus on cancer biology and early detection. Using my background in mathematics, I specialize in scalable and interpretable machine learning to extract meaningful insights from large datasets.

I collaborate with clinicians and researchers to apply computational methods to real-world biomedical challenges. My current projects involve integrating different data types, analyzing spatial patterns in tissue samples from multiplex imaging, and leveraging existing databases for cancer research.

Beyond cancer, my earlier work focused on modeling spatiotemporal dynamics. During my PhD, I developed models for predicting changes across space and time, with applications in epidemiology. Building on this work, I later modeled the spread of COVID-19 using demographic and socioeconomic data to understand its impact on different communities.