معرفی
Lipei Zhang is a researcher affiliated with the Department of Applied Mathematics and Theoretical Physics (DAMTP) at the University of Cambridge, contributing to the Cambridge Image Analysis research group. Their work focuses on advancing machine learning and deep learning techniques for medical imaging applications, particularly in healthcare diagnostics and biomedical engineering. Research interests include brain disease analysis, MRI reconstruction, tumour segmentation, Alzheimer's diagnosis, and multi-modal data integration.
Key technical contributions involve developing novel neural network architectures like Hypergraph Dynamic Adapters and Dual-Stage Distribution Adaptation (D2SA) for improving medical image processing efficiency. Zhang's work bridges computational methods with clinical challenges, addressing issues such as low-count PET denoising, glioma grading, and cross-manufacturer chest X-ray segmentation. These efforts aim to enhance diagnostic accuracy and accelerate healthcare AI applications.
Publications highlight expertise in implicit neural representations, biophysics-informed regularization, and population-based graph neural networks. The research portfolio reflects a strong emphasis on translating theoretical advancements into practical tools for medical practitioners, emphasizing both algorithmic innovation and clinical relevance.
