Huang Xiao

Dr. Huang Xiao holds a doctoral degree of Computer Science from the Technical University of Munich. He is also a visiting scholar at Stanford University. His main research interests include adversarial machine learning, reinforcement learning, anomaly detection, trusted AI, and AI applications in cybersecurity. Dr. Xiao has published several top-tier conference and journal papers in both the machine learning and security domains. He led the machine learning research group at Fraunhofer AISEC Institute in Munich, where he worked closely with leading industrial partners on a number of R&D projects in cybersecurity. He was also a research scientist at Bosch Center for Artificial Intelligence, leading a research project on optimal transport theory and imitation learning. With many years of experience in industrial-scale data analytics and machine learning systems, he led and managed science and engineering team that design and build machine learning systems to tackle different cybersecurity problems, e.g., phishing detection, network anomaly detection, malware analysis, and threat analysis, for large organisations.