معرفی
Fuyi Wang is a Research Fellow in AI and Data Analytics at RMIT University's Accounting, Info Sys & Supply Chain department (City Campus, Australia). She holds a Ph.D. in Information Technology from Deakin University (expected 2025). Her research focuses on privacy-preserving technologies, secure AI systems, federated learning, and robust data security frameworks. Notable contributions include cryptographic solutions for medical data security, privacy-enhanced federated learning, and secure biometric systems.
Her work has been published in top-tier venues such as IEEE TSC, TIFS, USENIX Security, and ICLR. Recent research themes emphasize backdoor attack mitigation in federated learning, trust-enhanced medical inference systems, and privacy-preserving algorithms for intelligent transport systems. She has held academic roles including Visiting Scholar at Singapore University of Technology and Design (2024–2025) and Casual Lecturer at Edvantage Institute (teaching data security, cryptography, and digital forensics).
Collaborative projects include federated learning defense frameworks (e.g., FedCT, FedWARD) and cross-cluster privacy solutions. Her publications consistently address real-world challenges in secure AI deployment, with a focus on balancing functionality and privacy preservation in distributed systems.
- Education: Ph.D. Information Technology, Deakin University (2021–2025)
- Key Contributions: Over 15 peer-reviewed publications since 2022, with 2023–2025 work focusing on federated learning security and medical AI privacy
- Teaching: Courses in data security, cryptography fundamentals, and digital forensics at undergraduate and graduate levels
- Labs/Teams: Engaged in interdisciplinary research bridging AI, cybersecurity, and healthcare applications
