Rate My Professor Lin Li

Dr. Li's research focuses on cybersecurity and privacy, physiological signal-based biometrics (such as PPG and rPPG methods), artificial intelligence-driven security analysis and vulnerability detection in software systems, and the intersection of large language models with cybersecurity. He has authored numerous publications in high-impact venues, including "The Security of Using Large Language Models: A Survey with Emphasis on ChatGPT" (IEEE/CAA Journal of Automatica Sinica, 2024, 85 citations), "Cyber Resilience in Healthcare Digital Twin on Lung Cancer" (IEEE Access, 2020, 154 citations), "A Hybrid Stacking Model for Enhanced Short-Term Load Forecasting" (Electronics, 2024, 73 citations), "SigA: rPPG-based Authentication for Virtual Reality Head-mounted Display" (RAID 2023), "Hiding Your Signals: A Security Analysis of PPG-based Biometric Authentication" (ESORICS 2023), "Video is All You Need: Attacking PPG-based Biometric Authentication" (AISec@CCS 2022, 26 citations), and "A Context-Aware Neural Embedding for Function-Level Vulnerability Detection" (Algorithms, 2021, 17 citations). His contributions have appeared in top conferences like ACM CCS, ESORICS, and RAID, demonstrating impact in the field. Dr. Li has received the Outstanding Teaching Excellence Awards 2025 from Southern Cross University and the ARC Discovery Project Scholarship (2021–2024). He serves as Local Organising Chair for AusDM 2024 and program committee member/reviewer for AAAI, ICLR, NeurIPS 2026, PAKDD 2025, IEEE TIFS, TDSC, and Computer & Security. As a Chief Investigator, he contributes to the project "Health status estimation and resilient closed-loop supply chain for retired electric vehicle batteries" (AEA Ignite, 334,052 AUD).