Aditya Surapaneni, PhD

I hold a PhD in mathematics and have experience as a data scientist in industry before transitioning to biostatistics and joining the faculty at the Department of Epidemiology at Johns Hopkins University.

• I analyze large administrative datasets of electronic health records to study real-world practice patterns, medication usage, and their impact, with a focus on kidney health.
• As a statistical programmer for the Chronic Kidney Disease Prognosis Consortium (CKD-PC), I work with data from over 20 million participants across 80+ cohorts worldwide and contribute to developing web-based risk calculators for CKD-PC models.
• In multi-omics research, I integrate large-scale datasets of metabolites, proteins, and genetic markers to identify disease biomarkers. My previous work includes genome-wide association studies and causal inference techniques such as Mendelian randomization.