Jiliu Zhou

Jiliu Zhou is an active academic researcher with a focus on medical imaging, artificial intelligence, and biomedical engineering. His work spans topics such as PET image reconstruction, radiotherapy dose prediction, and domain adaptation, often employing advanced deep learning techniques like GANs, Transformers, and diffusion models. Collaborations with experts like Yan Wang, Xi Wu, and Dinggang Shen highlight his interdisciplinary approach.

Research interests include

• Medical Imaging: Developing algorithms for PET and MRI reconstruction.
• Deep Learning: Applying GANs, Transformers, and diffusion models to medical data.
• Domain Adaptation: Enhancing robustness in multi-source environments.
• Image Processing: Innovating segmentation and super-resolution methods.

His recent publications demonstrate trends in semi-supervised learning, contrastive strategies, and multi-task frameworks for medical applications. Despite no explicit awards or grants mentioned, his prolific output in top journals and conferences underscores significant contributions to biomedical image analysis.