Biography
Dr. Cheng Ouyang is a departmental lecturer at the Institute of Biomedical Engineering, Department of Engineering Science. His research centres on data-efficient, robust, and user-friendly machine learning approaches for medical image/signal computing. His research topics include but are not limited to domain generalization, few-/zero-shot learning, uncertainty modeling, and multimodal machine learning for the interpretation and analysis of medical data, primally images including ultrasound, MRI, and CT. Prior to joining Oxford, he was a postdoctoral researcher at the Institute of Clinical Sciences, Imperial College London. He obtained his PhD from the Department of Computing at Imperial College London in 2023.
Research Interests
Multimodal machine learning for medical data (e.g., image, signal, and language). Domain generalization and uncertainty modeling for trustworthy machine learning in medical image computing (e.g., image reconstruction, classification, and segmentation). Few-/zero-shot learning for data-efficient machine learning in medical image computing. Machine learning for medical sciences (e.g., for the understanding of cardiovascular diseases).
