My research focuses on developing trustworthy and explainable artificial intelligence (AI) for medical diagnostics, with a particular emphasis on model calibration and reliability. I study how deep learning models can produce not only accurate but also well-calibrated and interpretable predictions that clinicians can trust in critical decision-making processes.

Ultimately, my goal is to build AI systems that are reliable, transparent, and generalizable across medical imaging modalities and clinical environments, enabling safe and responsible deployment of AI in healthcare.