Chin-Feng Lee

Over the past five years, Professor Lee's NSTC projects have focused on information security for digital images. Her research has enhanced the embedding capacity, image quality, and applicability of reversible information hiding techniques. She further integrated Variational Autoencoders (VAE) and Generative Adversarial Networks (GAN) to develop authentication frameworks capable of tampering detection, localization, and recovery. By introducing deep learning and self-referential imaging, she also developed a semi-blind watermarking technique that significantly strengthens the robustness and security of copyright protection. These projects are highly continuous and complementary, establishing a comprehensive image security framework encompassing data hiding, anomaly verification, and intelligent protection, while advancing AI applications in cybersecurity and digital content protection. In teaching, Professor Lee emphasizes a balance between theory and practice, and is committed to cultivating students’ skills in information application and data analysis. Through peer teaching observations, student feedback, and collaboration with industry, she continually refines course content and instructional strategies, actively promoting digital transformation and educational innovation.