Scholar-generated biography
Ka-Ho Chow is a researcher at The University of Hong Kong with expertise in Trustworthy AI, Cybersecurity, and the intersection of Machine Learning (ML) with Systems. His work focuses on enhancing the security and privacy of ML systems, particularly in federated learning and distributed training environments. He has published extensively on topics such as local differential privacy, adversarial attacks, and robust defense mechanisms against data leakage. His research also explores the application of ML in cybersecurity, including the development of secure systems for real-time object detection and blockchain-based fraud detection. Chow's contributions emphasize the importance of system-level design in ensuring the reliability and security of AI technologies.