Yu Huang

Yu Huang is a Researcher in the Department of Mathematical and Statistical Sciences at Clemson University's College of Science. His work focuses on advancing computational methods in medical imaging, computer vision, and deep learning applications. His research includes developing multimodal models for ophthalmology, enhancing 3D graphics rendering, and improving biomedical image analysis through active learning frameworks. Notable projects involve generative models for retinal imaging and shadow removal techniques in computer vision.

His research interests span computational ophthalmology, neural rendering, and AI-driven biomedical solutions. Recent efforts emphasize scalable diffusion models for high-resolution synthesis and robust medical image segmentation using test-time augmentation.

Yu Huang's publications reflect a strong emphasis on interdisciplinary research at the intersection of computer science and healthcare. His work addresses challenges in both foundational AI methodologies and their practical applications in clinical settings.