Research

Publications: Please visit Google Scholar.

Non-Invasive Temperature Measurement Within Cochlea

We strive to develop a high-resolution methodology for precise temperature measurement within the cochlea. This intricate work at the intersection of light-based therapies and temperature dynamics aims to unlock new dimensions in understanding and refining therapeutic interventions for auditory health.

Multiscale Reduced-Order Models of Cardiovascular Interventions

Employing advanced computational methodologies, we delve into the simulation of diverse cardiovascular scenarios, including prosthetic heart valves, transcatheter interventions, and atrial fibrillation ablation. Our approach extends beyond theoretical constructs, as we complement our computational models with in-vitro experimental setups. This integration of computational insights and real-world testing positions us to create reduced-order models that not only simulate intricate cardiovascular processes but also provide invaluable insights for the advancement of medical interventions and device design.

AI-Assisted Prediction of Medical Complications

Our research endeavors focus on extracting valuable insights to develop advanced AI models capable of predicting medical complications. By employing state-of-the-art data analytics techniques, we delve into the vast repositories of patient information to identify patterns, correlations, and predictive markers. Our commitment lies in bridging the gap between data and clinical outcomes, paving the way for personalized and anticipatory healthcare. Through the integration of machine learning algorithms, we aim to unravel the complexity of medical conditions, enabling early identification of potential complications and facilitating timely interventions. This innovative approach not only enhances our understanding of individual health trajectories but also holds the promise of significantly improving patient outcomes through proactive and data-driven medical care.