Research Projects

Medical Data Privacy and Security

Selected Publications

Le Vu Hieu. Efficient Homomorphic-Encryption-Based Privacy-Preserving Federated Learning System for MRI-Based AI Models. Undergraduate Thesis, Vietnam National University Hanoi, June 2026

Le Tuan Anh. Federated Multimodal Neuroimaging for Brain Age Prediction. Undergraduate Thesis, Vietnam National University Hanoi, June 2026

Xinguang Wang, Nguyen Linh Trung, Oliver Y. Chen, Alvaro Javier Vargas Guerrero, Quang Manh Doan, Tianzheng Hu, Stijn Denissen, Jeroen Van Schependom, and Guy Nagels. Federated adversarial network (FAN): A generative proxy-based, defense-enhanced, and non-iid-robust federated learning method. Image and Vision Computing, January 2026. [under review].

Nguyen Tien Dung. Adaptive Differential Privacy with Compression and Secure Aggregation for Federated Learning in Neuroimaging. Undergraduate Thesis, Vietnam National University Hanoi, December 2025

Xinguang Wang, Nguyen Linh Trung, Oliver Y. Chen, Jeroen Van Schependom, Stijn Denissen, and Guy Nagels. PDD-FANs: Personalized decentralized federated adversarial networks with defense mechanism in non-IID setting. In 2025 IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom), Guizhou, China, 17-21 November 2025.

SAME CATEGORY

Signal Processing for Machine Learning

Machine learning for signal processing

Tensor Decomposition for Medicine

Tensor decomposition (TD) is a powerful mathematical framework for analyzing high-dimensional and multi-way data, such as medical images, biomedical signals, and clinical measurements. Unlike conventional matrix-based methods, TD represents a tensor as a combination of lower-dimensional factor matrices or core tensors, enabling the extraction of latent structures while preserving the intrinsic multi-dimensional relationships within the […]