معرفی
Dr. Cheng Ouyang is a Departmental Lecturer at the University of Oxford's Institute of Biomedical Engineering, part of the Department of Engineering Science. Affiliated with St. Peter's College, his research focuses on developing data-efficient, robust machine learning approaches for medical imaging and signal analysis. Key interests include domain generalization, few-/zero-shot learning, uncertainty modeling, and multimodal learning applied to medical data such as ultrasound and MRI. Prior to Oxford, he conducted postdoctoral research in cardiac imaging at Imperial College London, where he also earned his PhD in Computing.
His work emphasizes practical medical applications, such as accelerating MRI reconstruction and enhancing ECG classification through multimodal techniques. Recent contributions include the CMRxRecon2024 dataset for cardiac MRI and federated learning approaches for low-dose CT denoising. His methods address challenges in generalizability, stability, and user interaction in clinical AI systems.
Awards and recognitions are pending explicit mentions in the text. Dr. Ouyang's research spans foundational machine learning theory and applied biomedical engineering, with a focus on bridging gaps between algorithmic innovation and clinical utility. His lab collaborates across disciplines to advance medical imaging analysis and decision support systems.
