Browse publications on Google Scholar (top-right) ↗
Resume (English only)
Academic Achievements
- The paper titled 'Clean-Label Physical Backdoor Attacks with Data Distillation' has been accepted at the Reliable ML from Unreliable Data workshop at NeurIPS 2025.
- The paper 'An Empirical Study of Federated Learning on IoT-Edge Devices: Resource Allocation and Heterogeneity' was accepted by IEEE Transactions on Neural Networks and Learning Systems (TNNLS).
- The work 'SC-GIR: Goal-oriented Semantic Communication via Invariant Representation Learning for Image Transmission' was accepted by IEEE Transactions on Mobile Computing (TMC).
- Several papers including HFedATM, pFedDSH, and FLAT were released on arXiv.
Research Experience
Located within VinUniversity's College of Engineering and Computer Science, the Security and Artificial Intelligence Lab (SAIL).
Background
Research interests include trustworthy AI, simplifying the development and deployment of machine learning models while ensuring their robustness, low-complexity generative approaches, strengthening algorithmic robustness, and addressing critical challenges in machine learning and federated learning to enhance security, privacy, efficiency, and fairness.
Miscellany
Looking for passionate new PhD students, Postdocs, and Master students to join the team.