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王新刚
职称/职务: Professor
电话: 029-81530845
传真: 029-81530845
电子信箱: wangxg@snnu.edu.cn
出生年月: November, 1975
办公地点: Zhizhi Bld #3521

XGW got his PhD degree from Beijing Normal University in 2002. His PhD thesis is about measure synchronization in coupled Hamiltonian systems, carried out at the Physics Department under the supervision of Prof. Gang Hu. After graduated, he joined the Temasek Laboratories at National University of Singapore as a research scientist, collaborating with Prof. Choy Heng Lai on research topics of chaos-based secure communications and complex network analysis. In 2008, he moved back to China and joined the Physics Department at Zhejiang University as a full professor, working on fusion plasma theory. In 2013, he joined the Physics Department at Shaanxi Normal University. His current research interest is mainly focusing on the collective behaviors emerged in coupled complex systems, and their implications to the functionality of the human brain and the artificial neural networks. He has published 110+ papers in peer-reviewed journals, including 40+ in physical review series (PRL, PRE and PRR) and 20+ in Chaos. The published works have been cited about 2500 times, with H-index=24. XGW is a “Qujiang” Professor in Shaanxi Normal University. In 2014, he received the "Shaanxi Youth Science and Technology Award". In 2017, he was awarded the title of "Leading and Innovative Talent in Science and Technology" by Shaanxi Province.

Teaching Jobs: 

        Mechanics (for undergraduate students), 

        Nonlinear Dynamics (for graduate students), 

        Complex Systems: An Introduction (for graduate students)

Research Interest: 

        Nonlinear Dynamics, Complex Networks, Computational Neuroscience,

        Pattern Formation, Machine Learning, Physics Education

ORCID iD: 0000-0002-6851-0109; 

A full publication list can be found at Google Scholar 

Publications in Recent 3 Years(*:Corresponding author) (Last update: 2024/9)

[1] Sansan Li and Xingang Wang*, “Resonance-induced synchronization in coupled phase oscillators with bimodal frequency distribution and periodic coupling”, Physical Review E 110, 024219 (2024).

[2] Yao Du, Qing Li, Huawei Fan, Meng Zhan, Jinghua Xiao, and Xingang Wang*, “Inferring attracting basins of power systems with machine learning”, Physical Review Research 6, 013181 (2024).    

[3] Haibo Luo, Yu Du, Huawei Fan, Xuan Wang, Jianzhong Guo, and Xingang Wang*, “Reconstructing bifurcation diagrams of chaotic circuits with reservoir computing”, Physical Review E 109, 024210 (2024).    

[4] Huawei Fan, Yafeng Wang, Yao Du, Haibo Qiu, and Xingang Wang*, “Scalable synchronization cluster in networked chaotic oscillators”, Chaos 34, 071102 (2024).

[5] Ya Wang, Liang Wang, Huawei Fan, Jun Ma, Hui Cao, and Xingang Wang*, “Breathing cluster in complex neuron–astrocyte networks”, Chaos 33, 113118 (2023).

[6] Huawei Fan, Ya Wang, and Xingang Wang*, “Eigenvector-based analysis of cluster synchronization in general complex networks of coupled chaotic oscillators”, Frontiers of Physics 18, 45302 (2023). (Cover Story).

[7] L. Wang, H. Fan, Y. Wang, J. Gao, Y. Lan, J. Xiao, and X. Wang*, "Inferring synchronizability of networked heterogeneous oscillators with machine learning", Physical Review E 107, 024314 (2023).

[8] Liang Wang, Huawei Fan, Jinghua Xiao, Yueheng Lan, and Xingang Wang*, “Criticality in reservoir computer of coupled phase oscillators”, Physical Review E 105, L052201(Letter) (2022).

[9Huawei Fan, Liang Wang, Yao Du, Yafeng Wang, Jinghua Xiao, and Xingang Wang*, “Learning the dynamics of coupled oscillators from transients”, Physical Review Research 4, 013137 (2022).

[10Ya Wang, Dapeng Zhang, Liang Wang, Qing Li, Hui Cao*, and Xingang Wang*, “Cluster synchronization induced by manifold deformation”, Chaos 32, 093139 (2022).

[11] Han Zhang, Huawei Fan, Yao Du, Liang Wang, and Xingang Wang*, “Anticipating measure synchronization in coupled Hamiltonian systems with machine learning”, Chaos 32, 083136 (2022).

[12Han Zhang, Huawei Fan, Liang Wang, and Xingang Wang*, “Learning Hamiltonian dynamics with reservoir computing,” Physical Review E 104, 024205 (2021).

[13] Huawei Fan, Ling-Wei Kong, Ying-Cheng Lai, and Xingang Wang*, “Anticipating synchronization with machine learning”, Physical Review Research 3, 023237 (2021).

[14] Bingwei Li, Yuan He, Linig-Dong Li, Lei Yang, and Xingang Wang*, “Spiral wave chimeras in reaction-diffusion systems: Phenomenon, mechanism and transitions”, Communications in Nonlinear Science and Numerical Simulation 99, 105830 (2021).

[15] Yali Guo, Han Zhang, Liang Wang, Huawei Fan, Jinghua Xiao, and Xingang Wang*, “Transfer learning of chaotic systems”, Chaos 31, 011104 (2021). (Fast track).

[16] Huawei Fan, Ling-Wei Kong, Xingang Wang, Alan Hastings, and Ying-Cheng Lai, “Synchronization within synchronization: transients and intermittency in ecological networks”, National Science Review, 8:nwaa269 (2021).
Highlights on National Science ReviewPhysics.orgScience Codex

 

 

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