Academic/Professional Qualifications：

[1]2010.9—2011.9 University of Massachusetts Medical School, mathematical modeling and biological data analysis, exchange doctoral student,

Supervisor: Prof. William Schwartz

[2]2008.9—2012.2 Physics Department of East China Normal University, Complex networks and nonlinear science, Doctor degree, Supervisor: Prof. Liu Zonghua

[3]2005.9—2008.7 Physics Department of Yangzhou University, complex networks and nonlinear science, Master degree, Supervisor: Prof. Jiang Yumei and He Daren

[4]2001.9—2005.7 Physics Department of Yangzhou University, Physical Education, Degree: Bachelor 

Career History

[3]2020.07— Now Business School of University of Shanghai for Science and Technology, Full Professor

[2]2015.05— 2020.06 Business School of University of Shanghai for Science and Technology, Associate Professor

[1]2012.04—2014.12 Leiden University Medical Centre, Netherlands, mathematical modeling and biological network data analysis

Researcher supervisor: Prof. Johanna H. Meijer

Representative Paper：

1. Chen X, Weng T, Gu C, & Yang H (2019) Synchronizing hyperchaotic subsystems with a single variable: A reservoir computing approach. Physica A534.

2. Chen X, et al. (2020) Mapping topological characteristics of dynamical systems into neural networks: A reservoir computing approach. Physical Review E 102(3).

3. Deng S, Ren H, Weng T, Gu C, & Yang H(2019) Information on evolutionary age in redundancy of complex network. Modern Physics Letters B 33(27).

4. Ding W, Gu C, & Liang X (2016) A Simple Structure for Signal Amplification. Communications in Theoretical Physics65(2):189-192.

5. Feng J & Gu C (2020) Scale invariance in the series of Chinese-character lengths. International Journal of Modern Physics C 31(1).

6. Feng W, Yang Y, Yuan Q, Gu C, & Yang H(2019) Evolution of scaling behaviors in currency exchange rate series. Fractals-ComplexGeometry Patterns And Scaling In Nature and Society 27(2).

7. Gao J & Gu C (2019) Super Multi-Armed and Segmented Spiral Pattern in a Reaction-Diffusion Model. Ieee Access 7: 140391-140401.

8. Gao J, Gu C, & Yang H (2020) Spiralwaves with interfacial oscillatory chemical reactions emerge in a model of reaction-diffusion systems. Chemical Physics 528.

9. Gao J, Gu C, & Yang H (2021) Applying a global pulse disturbance to eliminate spiral waves in models of cardiac muscle.Chinese Physics B 30(7).

10. Gao J, Gu C, Yang H, & Wang M (2021) A flight formation mechanism: The weight of repulsive force. Communications In Nonlinear Science And Numerical Simulation 95.

11. Gao J, Gu C, Yang H, & Weng T (2019) Sizeof a steady disturbance source affects the frequency of a target wave. AIPAdvances 9(8).

12. Gao J, Gu C, Yang H, & Weng T (2020)Excited state of spiral waves in oscillatory reaction-diffusion systems causedby a pulse. Physical Review E 101(4).

13. Gao J, Gu C, Yang H, & Weng T (2020)Prediction of spatial distribution of invasive alien pests in two-dimensionalsystems based on a discrete time model. Ecological Economics 143.

14. Gao J, Gu C, Yang H, & Weng T (2020) Atype of bi-stable spiral wave in a single -period oscillatory medium. CommunicationsIn Nonlinear Science And Numerical Simulation 85.

15. Gu C, et al. (2015) Lack of exercise leads tosignificant and reversible loss of scale invariance in both aged and youngmice. Proceedings of the National Academy of Sciences of the United States ofAmerica 112(8): 2320-2324.

16. Gu C, et al. (2019) Splitting between twosubgroups of the SCN neurons with instantaneous feedback. Nonlinear Dynamics97(2): 1245-1251.

17. Gu C, et al. (2019) Disassortative NetworkStructure Improves the Synchronization between Neurons in the SuprachiasmaticNucleus. Journal of Biological Rhythms 34(5): 515-524.

18. Gu C, Liang X, Yang H, & Rohling JHT(2016) Heterogeneity induces rhythms of weakly coupled circadian neurons.Scientific Reports 6.

19. Gu C, Liu Z, Schwartz WJ, & Indic P (2012)Photic Desynchronization of Two Subgroups of Circadian Oscillators in a NetworkModel of the Suprachiasmatic Nucleus with Dispersed Coupling Strengths. PLoSOne 7(5).

20. Gu C, Ramkisoensing A, Liu Z, Meijer J, &Rohling J (2014) The Proportion of Light-Responsive Neurons Determines theLimit Cycle Properties of the Suprachiasmatic Nucleus. Journal of BiologicalRhythms 29(1):16-27.

21. Gu C, Rohling J, Liang X, & Yang H (2016)Impact of dispersed coupling strength on the free running periods of circadianrhythms. Physical Review E 93(3).

22. Gu C, Tang M, Rohling J, & Yang H (2016)The effects of non-self-sustained oscillators on the en-trainment ability ofthe suprachiasmatic nucleus. Scientific Reports 6.

23. Gu C, Tang M, & Yang H (2016) Thesynchronization of neuronal oscillators determined by the directed networkstructure of the suprachiasmatic nucleus under different photoperiods.Scientific Reports 6.

24. Gu C, Wang J, & Liu Z (2009) Free-runningperiod of neurons in the suprachiasmatic nucleus: Its dependence on thedistribution of neuronal coupling strengths. Physical Review E 80(3).

25. Gu C, Wang J, Wang J, & Liu Z (2011)Mechanism of phase splitting in two coupled groups of suprachiasmatic-nucleusneurons. Physical Review E 83(4).

26. Gu C, Wang P, Weng T, Yang H, & Rohling J(2019) Heterogeneity of neuronal properties determines the collective behaviorof the neurons in the suprachiasmatic nucleus. Mathematical Biosciences andEngineering 16(4):1893-1913.

27. Gu C, Xu J, Liu Z, & Rohling J (2013)Entrainment range of nonidentical circadian oscillators by a light-dark cycle.Physical Review E 88(2).

28. Gu C, Xu J, Rohling J, Yang H, & Liu Z(2015) Noise Induces Oscillation and Synchronization of the Circadian Neurons.PLoS One 10(12).

29. Gu C & Yang H (2016) The circadian rhythminduced by the heterogeneous network structure of the suprachiasmatic nucleus.Chaos 26(5).

30. Gu C & Yang H (2017) The asymmetry of theentrainment range induced by the difference in intrinsic frequencies betweentwo subgroups within the suprachiasmatic nucleus. Chaos 27(6).

31. Gu C & Yang H (2017) Differences inintrinsic amplitudes of neuronal oscillators improve synchronization in thesuprachiasmatic nucleus. Chaos 27(9).

32. Gu C, Yang H, Meijer JH, & Rohling J(2018) Dependence of the entrainment on the ratio of amplitudes between twosubgroups in the suprachiasmatic nucleus. Physical Review E 97(6).

33. Gu C, Yang H, & Rohling J (2017)Dissociation between two subgroups of the suprachiasmatic nucleus affected bythe number of damped oscillated neurons. Physical Review E 95(3).

34. Gu C, Yang H, & Ruan Z (2017) Entrainmentrange of the suprachiasmatic nucleus affected by the difference in the neuronalamplitudes between the light-sensitive and light-insensitive regions. PhysicalReview E 95(4).

35. Gu C, Yang H, & Wang M (2017) Dispersionof the intrinsic neuronal periods affects the relationship of the entrainmentrange to the coupling strength in the suprachiasmatic nucleus. Physical ReviewE 96(5).

36. Gu C, Yang H, Wang M, & Rohling J (2019)Heterogeneity in relaxation rate improves the synchronization of oscillatoryneurons in a model of the SCN. Chaos 29(1).

37. Gu C, Wang P, & Yang H (2019) Entrainmentrange affected by the heterogeneity in the amplitude relaxation rate ofsuprachiasmatic nucleus neurons. Chinese Physics B 28(1).

38. Gu C, Yang H, & Wang M (2018) RatioBetween Sensitive Strength to Light Information and Coupling Strength AffectsEntrainment Range of Suprachiasmatic Nucleus. Communications in TheoreticalPhysics 70(6):771-776.

39. Gu C, Zhang X, & Liu Z (2014) Collectivebehaviors of suprachiasm nucleus neurons under different light-dark cycles. ChinesePhysics B 23(7).

40. Gu C, et al. (2011) Onset of cooperationbetween layered networks. Physical Review E 84(2).

41. Gu Q, Qin G, Wang Y, Gu C, & Yang H(2019) Scale-Invariance Exists in the Series of Character Intervals in the FourGreat Chinese Novels. Communications in Theoretical Physics 71(9):1139-1142.

42. Li J, Gu C, & Yang H (2020) Noise inducesoscillation in the two weakly coupled subgroups of the suprachiasmatic nucleus.Nonlinear Dynamics 102(4):2759-2766.

43. Li W, Jiang L, Gu C, & Yang H (2017) Theinfluence of migration speed on cooperation in spatial games. Journal ofStatistical Mechanics-Theory and Experiment.

44. Li W, Jiang L, Gu C, & Yang H (2018)Influentials promote cooperation in spatial snowdrift games. Journal ofStatistical Mechanics-Theory and Experiment.

45. Liu K, Weng T, Gu C, & Yang H (2020)Visibility graph analysis of Bitcoin price series. Physica A 538.

46. Liu Z, Xiao Q, Zhan Q, Gu C, & Yang H(2017) Network-based landscape of research strengths of universities inMainland China. Physica A 478:49-62.

47. Mutua S, Gu C, & Yang H (2016) Visibilitygraphlet approach to chaotic time series. Chaos 26(5).

48. Qiu L, Gu C, Xiao Q, Yang H, & Wu G (2018)State network approach to characteristics of financial crises. Physica A492:1120-1128.

49. Qiu L, Yang T, Yin Y, Gu C, & Yang H(2016) Multifractals embedded in short time series: An unbiased estimation ofprobability moment. Physical Review E 94(6).

50. Ramkisoensing A, et al. (2014) Enhanced PhaseResetting in the Synchronized Suprachiasmatic Nucleus Network. Journal ofBiological Rhythms 29(1):4-15.

51. Ren H, Yang Y, Gu C, Weng T, & Yang H(2018) A Patient Suffering From Neurodegenerative Disease May Have aStrengthened Fractal Gait Rhythm. IEEE Transaction on Neural Systems andRehabilitation Engineering 26(9):1765-1772.

52. Ren H, et al. (2020) Pattern interdependentnetwork of cross-correlation in multivariate time series. Physical ReviewApplied 384(30).

53. Ruan Z, Tang M, Gu C, & Xu J (2017)Epidemic spreading between two coupled subpopulations with inner structures.Chaos 27(10).

54. Song J, Weng T, Gu C, & Yang H(2020)Patterns of cross-correlation in time series: A case study of gait trails*. ChinesePhysics B 29(8).

55. Stephen M, Gu C, & Yang H (2015)Visibility Graph Based Time Series Analysis. PLoS One 10(11).

56. Wang Y, Ca X, Weng T, Yang H, & Gu C(2021) Lowest-degree preference random walks on complex networks. Physica A577.

57. Wang Y, Cao X, Weng T, Yang H, & Gu C(2021) A convex principle of search time for a multi-biased random walk oncomplex networks. Chaos Solitons & Fractals 147.

58. Wang Y, et al. (2014) An Automatic HighEfficient Method for Dish Concentrator Alignment. Mathematical Problems inEngineering 2014.

59. Wang Y, Weng T, Deng S, Gu C, & Yang H(2019) Sampling frequency dependent visibility graphlet approach to timeseries. Chaos 29(2).

60. Weng T, et al. (2020) Synchronization ofreservoir computers with applications to communications. Physica A 544.

61. Weng T, et al. (2021) Representing complexnetworks without connectivity via spectrum series. Information Sciences563:16-22.

62. Weng T, et al. (2019) Predator-prey games oncomplex networks. Communications In Nonlinear Science And Numerical Simulation79.

63. Weng T, Yang H, Gu C, Zhang J, & Small M(2019) Synchronization of chaotic systems and their machine-learning models.Physical Review E 99(4).

64. Wu G, Gu C, Qiu L, & Yang H (2017) Auniform framework of projection and community detection for one-mode network inbipartite networks. Chinese Physics B 26(12).

65. Wu G, Gu C, Qiu L, & Yang H (2018)Community detection based on preferred mode in bipartite networks. ModernPhysics Letters B 32(27).

66. Wu J, Zheng M, Wang W, Yang H, & Gu C(2018) Double transition of information spreading in a two-layered network.Chaos 28(8).

67. Wu J, Zheng M, Xu K, & Gu C (2020)Effects of two channels on explosive information spreading. Nonlinear Dynamics99(3):2387-2397.

68. Wu J, et al. (2018) A model of spreading ofsudden events on social networks. Chaos 28(3).

69. Xu J, Gu C, Pumir A, Garnier N, & Liu Z(2012) Entrainment of the suprachiasmatic nucleus network by a light-darkcycle. Physical Review E 86(4).

70. Yang H, Gu C, Tang M, Cai S-M, & Lai Y-C(2019) Suppression of epidemic spreading in time-varying multiplex networks. AppliedMathematical Modelling 75:806-818.

71. Yang T, Gu C, & Yang H (2016) Long-RangeCorrelations in Sentence Series from A Story of the Stone. PLoS One 11(9).

72. Yang Y, Gu C, Xiao Q, & Yang H (2017)Evolution of scaling behaviors embedded in sentence series from A Story of theStone. PLoS One 12(2).

73. Yang Y, et al. (2017) Scaling invarianceembedded in very short time series: A factorial moment based diffusion entropyapproach. Chinese Journal of Physics 55(6):2325-2335.

74. Yu X, Weng T, Gu C, & Yang H (2020)Comparison of gene regulatory networks to identify pathogenic genes for lymphoma.Journal of Bioinformatics and Computational Biology 18(5).

75. Yuan Q, Gu C, Weng T, & Yang H (2018)Unbiased detrended fluctuation analysis: Long-range correlations in very shorttime series. Physica A 505:179-189.

76. Yuan Q, et al. (2021) Multi-scale transitionmatrix approach to time series. Physica A 578.

77. Zhang K, et al. (2021) Synchronization ofchaotic systems and long short-term memory networks by sharing a singlevariable. Modern Physics Letters B 35(6).

78. Zhao Y, Gu C, & Yang H (2021) Visibility-graphletapproach to the output series of a Hodgkin-Huxley neuron. Chaos 31(4).

79. Zhou L, Qiu L, Gu C, & Yang H (2018)Immediate causality network of stock markets. EPL 121(4).

80. Zhu B, Zhou J, Jia M, Yang H, & Gu C(2020) Entrainment range affected by the difference in sensitivity tolight-information between two groups of SCN neurons. Chinese Physics B 29(6).

81. ZhouJ, Gu C, Zhu B, Yang H, & Rohling J,(2022) Poincare model shows howheterogeneity in light sensitivity can alter circadian clock function. Communicationsin Nonlinear Science and Simulation 111.

82. WangJ, Gu C, & Ji P (2022) Frequency-amplitude correlation inducing first-orderphase transition in coupled oscillators. New Journal of Physics 24(7).

83. Yan S,Li S, Wang H, Gu C, & Yang H (2022) Structure of cross-correlation betweenstock and oil markets. EPL 138(6).

84. WangH, et al.(2022) Epidemic dynamics on higher-dimensional small world networks.Applied Mathematics and Computation 421.

85. ChenS, et al. (2022) A Nonlinear Time-Series Analysis to Identify the Thresholds inRelationships Between Antimicrobial Consumption and Resistance in a ChineseTertiary Hospital. Infectious Diseases and Therapy 11(3): 1019-1032.

86. Liu Y,et al. (2022) Families' influence on romantic relationship and itsreconstruction. Chaos Solitions & Fractals 155.

87. Wu G,Gu C, & Yang H (2022) A spectral method of modularity for communitydetection in bipartite networks. EPL 137(3).

88. ZhengW, Gu C, Yang H, & Rohling J (2022) Motif structure for the four subgroupswithin the suprachiasmatic nuclei affects its entrainment ability. PhysicalReview E 105(1).

89. Gao J,Wang X, Gu C, Shen C, & Yang H (2022) Irregular spots on body surfaces of vertebrates induced by supercritical pitchfork bifurcations. Chaos 32(1).

90. ShereheS, Wan H, Gu C, & Yang H (2022) Information flow between stock markets: AKoopman decomposition approach. Chinese Physics B 31(1).

91. WangP, Gu C, Yang H, & Wang H (2022) Identify the characteristic in theevolution of the causality between the gold and dollar. Electronic ResearchArchive 30(9): 3660-3678.

92. Gu C,Li J, Zhou J, Yang H, & Wang M (2022) Strengthen the circadian rhythms bythe mathematical model of the SCN. European Physical Journal Special Topics 231(5):827-832.

93. Gao J,Gu C, Shen C, & Yang, H (2021) Spiral waves in population densitydistributions of invasive pests in warm-temperate deciduous forest ecosystems. EPL136(3).

94. Cao X,et al. (2021) One-Step Memory Random Walk on Complex Networks: An EfficientLocal Navigation Strategy. Fluctuation and Noise Letters 20(5).

Project：

Chaired National Natural Science Foundation No.11505114 （2016.01-2018.12）

Chairing National Natural Science Foundation No.11875042 （2019.01-2022.12）

Undergraduates:《Data structure》、《Introduction to systems engineering》、《Statics》、《Fundamentals of artificial intelligence》、《Econometrics》.

Member of a council for shanghai Nonlinear Science Research Association

Anonymous reviewer for more than ten SCI journals 

Young Oriental Scholar of Shanghai Universities

Zhiyuan Scholar of USST