Research Background & Expertise

I am a Ph.D. candidate in Applied Mathematics with research interests at the intersection of biostatistics, computational mathematics, and healthcare technology. My work focuses on developing digital twin frameworks for healthcare systems that integrate mathematical modeling, data assimilation, and medical imaging to enable predictive, personalized, and data-driven healthcare solutions.

My technical expertise includes Kalman Filter and Ensemble Kalman Filter–based data assimilation, uncertainty quantification, and computational modeling of complex biological systems. I am particularly interested in incorporating medical imaging data into dynamic models to improve state estimation, disease monitoring, and treatment optimization. My research is grounded in applied mathematics and emphasizes scalable, interpretable, and reliable computational methods suitable for real-world clinical environments.