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Zheng-Meng Zhai (翟正蒙) is a Ph.D. student in Prof. Ying-Cheng Lai’s chaos research group at Arizona State University. His background is in physics and electrical engineering, with a strong interest in nonlinear dynamics and chaos, machine learning and neural networks, as well as time series analysis. His research primarily focuses on solving problems in nonlinear dynamics using machine learning. His current research interests include: Inverse modeling with machine learning, such as parameters extraction/trackingNonlinear trajectory tracking control using machine learningMachine learning applications in magnetic navigationReservoir computing mechanisms and properties, and their relationship to the brainChaotic systems short- and long-term prediction by machine learningRecent NewsFeb. 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. Highlighted as a Featured ArticleAug. 24, 2023. Paper entitled “Emergence of a resonance in machine learning” published in Physical Review Research.Mar. 9, 2023. Paper entitled “Detecting Weak Physical Signal from Noise: A Machine-Learning Approach with Applications to Magnetic-Anomaly-Guided Navigation” published in Physical Review Applied.ServicesJournal Reviewer: Physical Review X, Physical Review X Energy, IEEE Transactions on Neural Networks and Learning Systems, IEEE Transactions on Artificial Intelligence, Information Fusion, Information Sciences, IEEE Access, Plos One.Contact InformationZheng-Meng Zhai School of Electrical, Computer and Energy Engineering Arizona State University Tempe, Arizona 85281 Email: [email protected], [email protected] |
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