DrTao Zhou

Dr. Tao received his PhD degree from Curtin University, Australia in 2019. He is an active researcher in computational intelligence, focusing on bridging the critical gap between theretical AI and tangible industrial and societal impact. His core research advances latent representation-based reinforcement learning and data-driven algorithms, addressing complex system dynamics in decision-making. He works as a translational architect, engineering robust intelligent algorithms capable of navigating the uncertainties of real-world applications,  including intelligent systems in engineering and healthcare. 

At IISRI, Dr. Tao lead high-impact, industry-embedded projects across diverse domains. His applied portfolio includes advanced vision-based systems for intelligent transport, AI-driven sustainable industrial process optimisation, and multi-modal AI for digital health systems. His research has published in high-impact outlets, including top-tier journals such as IEEE Transactions on Neural Networks and Learning Systems, IEEE Transactions on Evolutionary Computation, IEEE transactions on Intelligent Transport Systems and Expert Systems with Applications.

My current research areas and interests: 

• Offline-Online Constrained Reinforcement Learning 
• Latent Representation Learning for Dynamics Modelling 
• Koopman Operator in Optimal Control 
• Multi-modal Human Motion Understanding
• Intelligent Algorithms for Operations Research