Hi! I am Zheng-Meng Zhai (翟正蒙), a fifth-year Ph.D. student in Prof. Ying-Cheng Lai’s chaos group at Arizona State University.

I received my Bachelor’s degree in Electronic Information Science and Technology from Southwest Jiaotong University, and my Master’s degree in Theoretical Physics from East China Normal University, where I was advised by Prof. Ming Tang. My background is in physics and electrical engineering, with research focus on combining machine learning with nonlinear dynamics. My current research projects include:

• System dynamics recovery using hybrid transformer and reservoir computing methods
• Model-free nonlinear control
• Machine learning mechanisms and physics-inspired machine learning
• Chaotic systems forecasting with machine learning

Recent News

• Dec. 17, 2025. Paper entitled “Learning to learn ecosystems from limited data” published in PNAS.
• Aug. 28, 2025. Paper entitled “Bridging known and unknown dynamics by transformer-based machine-learning inference from sparse observations” published in Nature Communications.
• May. 11, 2025. Travel. SIAM Conference on Applications of Dynamical Systems. Denver, Co.
• Mar. 16, 2025. Travel. APS March Meeting. Anaheim, CA.
• Feb. 4, 2025. Paper entitled “Detecting Attacks and Estimating States of Power Grids from Partial Observations with Machine Learning” published in PRX Energy.
• Nov. 7, 2024. Travel. MURI project kickoff meeting. Yale University, New Haven.
• Jul. 30, 2024. Paper entitled “Machine-learning nowcasting of the Atlantic Meridional Overturning Circulation” published in APL Machine Learning.
• Feb. 23, 2024. Paper entitled “Machine-learning parameter tracking with partial state observation” published in Physical Review Research.
• Sept. 14, 2023. Paper entitled “Model-free tracking control of complex dynamical trajectories with machine learning” published in Nature Communications. \(\rm {\color{tomato} {Highlighted \ as \ a \ Featured \ Article}}\) in Applied Physics and Mathematics.

Services

Journal Reviewer:

Nature Machine Intelligence, Nature Communications,

Physical Review X, PRX Energy, Physical Review Research, Physical Review Applied, Physical Review E,

IEEE Transactions on Artificial Intelligence,  IEEE Transactions on Emerging Topics in Computational Intelligence,  IEEE Transactions on Neural Networks and Learning Systems,

Neural Networks, New Journal of Physics, Nonliear Dynamics, APL Machine Learning, Chaos, npj Complexity, etc;

Contact Information

Zheng-Meng Zhai

School of Electrical, Computer and Energy Engineering

Arizona State University

Tempe, Arizona 85281

Email: zhaizhengmeng@gmail.com, zzhai6@asu.edu