KCDS Virtual Open House 2025 - Project 02 - Developing Dynamic Digital Twins of the Human Heart

Cardiovascular diseases are the world’s leading cause of death, with atrial fibrillation (AF) a major contributor. AF often stems from atrial cardiomyopathy—progressive structural and electrical remodeling of the heart’s atria. Current diagnostic tools provide only static or invasive insights, limiting our ability to monitor disease evolution or tailor therapies.

This doctoral project aims to transform static “digital snapshots” of the heart into longitudinal digital twins—personalized, dynamic models that evolve with the patient. By combining data assimilation, uncertainty quantification, and computational cardiac modeling and simulation, the project will integrate invasive electro-anatomic maps with non-invasive surface ECGs to reconstruct and continuously update patient-specific atrial properties.

Within a Bayesian framework, advanced filtering methods (e.g., ensemble Kalman filters) will be developed to fuse noisy, sparse clinical data with physics-based cardiac models. This approach will enable accurate estimation of hidden physiological parameters and capture disease progression over time.

The doctoral candidate will work at the intersection of mathematical modeling, scientific computing, and cardiovascular science, jointly supervised by the Krumscheid group (uncertainty quantification and data assimilation) and the Loewe group (computational cardiology and simulation). ... mehrThe project offers an exciting opportunity to contribute to next-generation personalized medicine and digital health.