I utilize computational and machine learning methods to identify genetic and epigenetic signatures associated with aging and cancer.
During my postdoctoral training, I transitioned my research focus to the single-cell level, specifically delving into the investigation of epigenetic patterns in Acute Myeloid Leukemia (AML) within the context of aging. Additionally, I am working on establishing correlations between somatic mutations and these epigenetic changes. This in-depth analysis, which combines multiple types of biological data, has the potential to facilitate early detection, treatment, and prevention of AML in the aging population. We are fortunate to be in an era where biological data is exponentially increasing, awaiting deciphering. The analysis of such vast datasets necessitates the development of novel computational methodologies, a realm I am actively exploring in my postdoctoral research.