Ph.D. (Nanyang Technological University)

B.S. (University of Science and Technology of China)

Professor Zhu Xi earned a Bachelor's degree in Applied Physics from the Special Class for the Gifted Young (SCGY) at the University of Science and Technology of China and Ph.D. in Materials Science and Engineering from Nanyang Technological University in Singapore. Professor Zhu Xi has been engaged in experimental verification of AI and robotics technology for fundamental physics and chemistry theories. In late 2017, Professor Zhu joined School of Science and Engineering and the Robotics and Artificial Intelligence Laboratory (RAIL) at The Chinese University of Hong Kong, Shenzhen. In 2018, he delivered China's first chemical experiment robot, AIR-Chem (Authentic Intelligent Robotics for Chemistry). Subsequently, he developed various intelligent laboratory architectures, including the MAOS (Materials Acceleration Operating System) operating system, the cloud-based chemical materials laboratory MAOSIC, the intelligent experiment system AIM (Authentic Intelligent Machine) with autonomous experimental data analysis capabilities, the hyper-converged autonomous organic continuous flow reaction infrastructure HAORI, the blockchain-integrated automatic experiment platform BiaeP, and more than 10 other intelligent laboratory architectures. Additionally, he developed AI-Supervisor system and the materials chemistry research and teaching metaverse system Mateverse. As an expert in the interdisciplinary field of AI robotics technology and chemical materials, he published the world's first book on the technical principles and scenario analysis of AI robotics technology in materials science, titled "AI and Robotic Technology in Materials and Chemistry Research, ISBN: 978-3-527-35428-3".

1. Gao, Y.; Lin, H.; Zhu, X. General Aqueous System Simulation through an AI-Embedded Metaverse Chemistry Laboratory. The Journal of Physical Chemistry Letters 2024, 15, 5978-5984.
2. Zhu, X. Toward the Uniform of Chemical Theory, Simulation, and Experiments in Metaverse Technology. Precision Chemistry 2023, 1 (4), 192-198.
3. Xu, Y.; Ye, S.; Zhu, X. The ScholarNet and Artificial Intelligence (AI) Supervisor in Material Science Research. The Journal of Physical Chemistry Letters 2023, 14 (36), 7981-7991.
4. Liu, R.; Li, J.; Xiao, S.; Zhang, D.; He, T.; Cheng, J.; Zhu, X. Authentic Intelligent Machine for Scaling Driven Discovery: A Case for Chiral Quantum Dots. ACS Nano 2022, 16 (1), 1600-1611.
5. Lin, H.; Ye, S.; Zhu, X. Geometry Orbital of Deep Learning (GOODLE): A uniform carbon potential. Carbon 2022, 186, 313-319.
6. Gao, Y.; Lu, Y.; Zhu, X. Mateverse, the future materials science computation platform based on metaverse. The Journal of Physical Chemistry Letters 2022, 14 (1), 148-157.
7. Liu, R.; Zhu, X. Essentiality of the Basis Function in Deep Learning Physical Chemistry Properties. The Journal of Physical Chemistry Letters 2021, 12 (27), 6330-6335.
8. Lu, Y.; Xu, Y.; Zhu, X. Designing and Implementing VR2E2C, a Virtual Reality Remote Education for Experimental Chemistry System. Journal of Chemical Education 2021, 98 (8), 2720-2725.
9. Li, J.; Tu, Y.; Liu, R.; Lu, Y.; Zhu, X. Toward “on‐demand” materials synthesis and scientific discovery through intelligent robots. Advanced Science 2020, 7 (7), 1901957.
10. Li, J.; Li, J.; Liu, R.; Tu, Y.; Li, Y.; Cheng, J.; He, T.; Zhu, X. Autonomous discovery of optically active chiral inorganic perovskite nanocrystals through an intelligent cloud lab. Nature communications 2020, 11 (1), 2046.