Mathematics-driven AI with practical impact.

I am an Assistant Professor and researcher working at the intersection of mathematics, machine learning, computer vision, medical imaging, and quantum computing.

My research focuses on mathematically grounded, reliable, and interpretable learning systems for challenging real-world applications. I am particularly interested in medical image analysis, hybrid classical–quantum learning, explainability, uncertainty estimation, calibration, and adaptive intelligent systems.

Alongside research, I teach programming, machine learning, big data analytics, statistics, and quantum computing, and mentor students in emerging areas of artificial intelligence and applied mathematics.