We do foundational work in machine learning, optimization, data mining, representation learning, and explainable AI, and we apply AI to address challenges in biomedical imaging, clinical decision making, signal processing, and immersive technologies.

We develop quantitative and AI-based tools that help clinicians and researchers quickly and accurately analyze images of the brain, lungs, and heart from advanced imaging technologies, such as computed tomography (CT), ultrasound, and positron emission tomography (PET).

We combine learning-based methods with techniques such as image segmentation and feature extraction, as well as time-series analysis and signal characterization, to automatically identify meaningful structures, detect patterns, classify signals, and make predictions from large or noisy datasets.

We are pioneering next-generation semiconductor electronics and photonics that will fundamentally transform everyday devices, from advancing quantum computing capabilities to enabling sophisticated modular sensors for IoT applications. We also explore the potential of biophotonics to revolutionize medicine, from creating non-invasive surgical tools to developing new ways to study human tissue for advanced diagnostics.