Jack Murdoch Moore
School of Physics Science and Engineering
Tongji University
67 Chifeng Road, Yangpu
Shanghai, China
Email: jackmoore AT tongji DOT edu DOT cn
Telephone: +86 (021) 65983380
Biography
I am a postdoctoral researcher in the research team of Prof. Gang Yan at the School of Physics Science and Engineering, Tongji University, Shanghai, China. I received my B.Sc. and Ph.D. degree at the University of Western Australia in 2013 and 2018 respectively. I grew up in Rockingham, Western Australia, a city whose neighbouring islands host penguins and sea lions.
I am interested in statistical physics, complex systems, network science, nonlinear time series analysis, and Chinese culture. My Chinese name is 墨龙明 (Mò Lóngmíng), and I am usually called Jack or 小明 (Xiǎomíng).
Publications
Google Scholar profile
- J. M. Moore, X. Zhang, G. Yan*, J. M. Moore*, “Foresight and relaxation enable efficient control of nonlinear complex systems,” Physical Review Research, vol. 5, no. 3, p. 033138, 2023.
- J. M. Moore, H. Wang, M. Small, G. Yan*, H. Yang, and C. Gu, “Correlation dimension in empirical networks,” Physical Review E, vol. 107, no. 3, p. 034310, 2023.
- X.-J. Zhang, J. M. Moore, G. Yan*, X. Li*, “Universal structural patterns in sparse recurrent neural networks,” Communications Physics, vol. 6, no. 1, p. 243, 2023.
- X. Ru, J. M. Moore, X. Y. Zhang, Y. Zeng, and G. Yan*, “Inferring Patient Zero on Temporal Networks via Graph Neural Networks,” Proceedings of the AAAI Conference on Artificial Intelligence, vol. 37, no. 8, p. 9632, 2023.
- P. Wang, C. Gu*, H. Yang, H. Wang, and J. M. Moore, “Characterizing systems by multi-scale structural complexity,” Physica A: Statistical Mechanics and its Applications, vol. 609, p. 128358, 2023.
- L. Liu, S. Chen*, M. Small, J. M. Moore, K. Shang, “Global stability and optimal control of epidemics in heterogeneously structured populations exhibiting adaptive behavior,” Communications in Nonlinear Science and Numerical Simulation vol. 126, p. 107500, 2023.
- J. M. Moore, G. Yan*, and E. G. Altmann, “Nonparametric power-law surrogates,” Physical Review X, vol. 12, p. 021056, 2022.
- H. Wang, J. M. Moore*, M. Small, J. Wang, H. Yang, and C. Gu, “Epidemic dynamics on higher-dimensional small world networks,” Applied Mathematics and Computation, vol. 421, p. 126911, 2022.
- H. Wang, Z. Du*, J. M. Moore*, H. Yang, and C. Gu, “Causal networks reveal the response of Chinese stocks to modern crises,” Information Sciences, vol. 609, p. 1670, 2022.
- L. Cui, J. M. Moore*, “Causal network reconstruction from nonlinear time series: A comparative study,” International Journal of Modern Physics C, vol. 32, no. 4, p. 1, 2021.
- J. M. Moore*, M. Small, and G. Yan, “Inclusivity enhances robustness and efficiency of social networks,” Physica A: Statistical Mechanics and its Applications, vol. 563, p. 125490, 2021.
- H. Wang, J. M. Moore, J. Wang*, and M. Small, “The distinct roles of initial transmission and retransmission in the persistence of knowledge in complex networks,” Applied Mathematics and Computation, vol. 392, p. 125730, 2021.
- D.C. Corrêa, J. M. Moore*, T. Jüngling, and M. Small, “Constrained Markov order surrogates,” Physica D: Nonlinear Phenomena, vol. 406, p. 132437, 2020.
- J. M. Moore*, D. M. Walker, and G. Yan, “Mean local autocovariance provides robust and versatile choice of delay for reconstruction using frequently sampled flowlike data,” Physical Review E, vol. 101, no. 1, p. 012214, 2020.
- K. K Shang*, B. Yang, J. M. Moore, Q. Ji, and M. Small, “Growing networks with communities: A distributive link model,” Chaos: An Interdisciplinary Journal of Nonlinear Science, vol. 30, no. 4, p. 041101, 2020.
- X. Peng, M. Small, Y. Zhao*, and J. M. Moore, “Detecting and predicting tipping points,” International Journal of Bifurcation and Chaos, vol. 29, no. 8, p. 1930022, 2019.
- H. Wang, J. Wang*, M. Small, and J. M. Moore, “Review mechanism promotes knowledge transmission in complex networks,” Applied Mathematics and Computation, vol. 340, p. 113, 2019.
- J. M. Moore, D.C. Corrêa*, and M. Small, “Is Bach’s brain a Markov chain? Recurrence quantification to assess Markov order for short, symbolic, musical compositions,” Chaos: An Interdisciplinary Journal of Nonlinear Science, vol. 28, no. 8, p. 085715, 2018.
- J. M. Moore* and M. Small, “Estimating dynamical dimensions from noisy observations,” Information Sciences, vol. 462, p. 55, 2018.
- J. Moore*, A. Karrech, M. Small, E. Veveakis, and K. Regenauer-Lieb, “Dissipative propagation of pressure waves along the slip-lines of yielding material,” International Journal of Engineering Science, vol. 107, p. 149, 2016.
- J. M. Moore*, A. Karrech, and M. Small, “Improvements to local projective noise reduction through higher order and multiscale refinements,” Chaos: An Interdisciplinary Journal of Nonlinear Science, vol. 25, no. 6, p. 063114, 2015.
Projects
- J. M. Moore, “Uncovering and evaluating the empirical laws of complex systems,” Ministry of Science and Technology of China, Foreign Young Talents Program, 2023.
- J. M. Moore, “Causal network inference for realistically nonlinear and non-separable complex systems,” National Natural Science Fund of China, Research Fund for International Young Scientists, grant no. 12150410309, 2022.