中文版 Wen-Xu Wang's Group (王文旭)
Director of the Center for Complexity Science
Professor in School of Systems Science, Beijing Normal University, Beijing, China, 100087
Office: Sci. & Tech. Building B517, Bejing Normal University
Visiting Professor in School of Electrical, Computer and Energy Engineering, Arizona State University, Tempe, Arizona 85287, USA
E-mail: wenxuwang(at)bnu(dot)edu(dot)cn; wenxuw(at)gmail(dot)com
Phone: (86)-10-58807084; (86)-18611812579
Wen-Xu Wang received B.S. and Ph.D. degrees in theoretical physics from University of Science and Technology of China in 2002 and 2007, respectively. From 2007-2008 he was a post-doctoral fellow in the Department of Electrical Engineering at Hong Kong City University. From 2008-2010, he continued his post-doctoral research in the Department of Electrical Engineering at Arizona State University. From 2010-2011, he became an Asistant Research Professor at the School of Electrical Engineering. In 2012, he was selected into the 1000 young talent program from Chinese government and joined Beijing Normal Univerisity, School of Systems Science, as a full professor. Now he is the director of the center for complexity science.
Wen-Xu Wang's research focus is on complex systems and nonlinear dynamics, mainly in the field of complex networks, biological physics, human behaviors and neural science. Recently, his group has developed a general framework to quantify the exact controllability of complex networks, and a general paradigm based on compressive sensing to reconstruct complex networks and nonlinear dynamics from extremely short time series. The researches have been published in Nat. Commun., PNAS, Phys. Rev. Lett., Phys. Rev. X, Phys. Rep. J. R. Soc. Interface, Sci. Rep., Phys. Rev. E and EPL, etc.. He has published over 120 papers in refereed journals. His current H-index is 35. He serves as the editoral board member of Sci. Rep., R. Soc. Open Science, and etc., and is also the referee of more than 30 research journals, including Nature Communications, Phys. Rev. Lett., J.Theo.Bio and IEEE Trans.Neural Networks, and etc.
- Xiao-Yong Yan, Wen-Xu Wang*, Zi-You Gao*, and Ying-Cheng Lai*,
"Universal model of individual and population mobility on diverse spatial scales",
Nature Communications 8, 1639 (2017). Supplementary Information. Research highlights: https://www.sciencedaily.com/releases/2017/11/171121095158.htm
- Ruiqi Li, Lei Dong, Jiang Zhang*, Xinran Wang, Wen-Xu Wang*, Zengru Di, and H. Eugene Stanley*,
"Simple spatial scaling rules behind complex cities",
Nature Communications 8, 1841 (2017). Supplementary Information.
- Boris Podobnika*, Marko Jusupg, Zoran Tiganjh, Wen-Xu Wang, Javier M. Buldu, and H. Eugene Stanley*,
"Biological conservation law as an emerging
functionality in dynamical neuronal networks",
Proc. Natl. Acad. Sci. USA 114, 11826-11831 (2017). Supplementary Information.
- Xiao Han, Shinan Cao, Zhesi Shen, Boyu Zhang*, Wen-Xu Wang*, Ross Cressman, H. Eugene Stanley*,
"Emergence of Communities and Diversity in Social Networks",
Proc. Natl. Acad. Sci. USA 114, 2887-2891 (2017). Supplementary Information.
- Wen-Xu Wang, Ying-Cheng Lai*, and Celso Grebogi,
"Data Based Identification and Prediction of Nonlinear and
Complex Dynamical Systems",
Physics Reports 664, 1 (2016).
- Le-Zhi Wang, Ri-Qi Su, Zi-Gang Huang, Xiao Wang, Wen-Xu Wang, Celso Grebogi, and Ying-Cheng Lai,
"A geometrical approach to control and
controllability of nonlinear dynamical networks",
Nature Communications 7, 11323 (2016). Supplementary Information.
- Xiao Han, Zhesi Shen, Wen-Xu Wang*, and Zengru Di,
"Robust Reconstruction of Complex Networks from Sparse Data",
Phys. Rev. Lett. 114, 028701 (2015). Supplementary Information.
- Xiao-Yong Yan, Chen Zhao, Ying Fan, Zengru Di, and Wen-Xu Wang*,
"Universal predictability of mobility patterns in cities",
J. R. Soc. Interface 11, 20140834 (2014). Supplementary Information.
Cover story: http://rsif.royalsocietypublishing.org/content/11/100.cover-expansion
- Zhesi Shen, Wen-Xu Wang*, Ying Fan, Zengru Di, and Ying-Cheng Lai,
"Reconstructing propagation networks with natural diversity and identifying hidden sources",
Nature Communications 5, 4323 (2014). Supplementary Information.
Highlighted by Natl. Sci. Rev.: Towards data-driven identification and control of complex networks.