معرفی
J. Huang is a faculty member at the Faculty of Electrical Engineering, Mathematics and Computer Science at Delft University of Technology. Their research is centered on federated learning, cybersecurity, and distributed systems, with a strong emphasis on defending against adversarial attacks and ensuring robustness in decentralized machine learning environments.
Research Interests:
- Federated Learning and Distributed AI
- Adversarial Attacks and Defenses
- Data Poisoning and Model Robustness
- Generative Adversarial Networks (GANs)
- Privacy-Preserving Machine Learning
- Trustworthy and Secure AI Systems
Recent publications reflect a deep engagement with security challenges in federated learning, including gradient inversion attacks, model poisoning without data access, and optimizing client selection strategies. These works contribute to advancing the reliability and safety of distributed AI systems.
Scientific Contributions: While no explicit awards are listed, the high citation counts and peer-reviewed contributions in top-tier venues like FC, SRDS, DSN, and PAKDD demonstrate significant academic impact.
Collaborations: Huang collaborates with researchers such as Z. Zhao, L.Y. Chen, S. Roos, C. Hong, and others, indicating a strong international research network, particularly within Europe and Asia.
