刘静

个人信息:Personal Information

教授 博士生导师 硕士生导师

性别:女

毕业院校:西安电子科技大学

学历:博士研究生毕业

学位:博士学位

在职信息:在职

所在单位:人工智能学院

所属院系: 人工智能学院

学科:计算机科学与技术 模式识别与智能系统

办公地点:北校区主楼III-409

联系方式:neouma@mail.xidian.edu.cn

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个人简介:Personal Profile

刘静,女,西安电子科技大学人工智能学院教授、博士生导师,海棠七号书院院长。分别于2000年与2004年在西安电子科技大学获得学士与博士学位,2009年破格晋升为教授。期间于2007年4月至2008年4月在澳大利亚昆士兰大学做博士后、2009年7月至2011年7月在澳大利亚新南威尔士大学国防研究院做研究员。

长期从事智能计算、复杂网络与大数据处理领域的研究工作,已合作出版英文专著3部、中文专著2部、发表国际期刊论文90余篇、国际会议论文70余篇。现为人工智能领域顶级期刊《IEEE Trans. Evolutionary Computation》副编,2017-2018任IEEE智能计算学会涌现科技技术委员会主席。

已主持多项国家级、省部级科研项目。2013年作为第三完成人获得国家自然科学二等奖,2014年获得吴文俊人工智能科学技术创新二等奖(个人奖),2015年获得国家自然科学基金优秀青年科学基金资助,2018年入选国家“万人计划”科技创新领军人才,同年被批准为享受国务院特殊津贴专家。

 


招生说明:

本人选择博士生、硕士生的条件是要有积极主动进取的学习态度,能全身心地投入到科研工作中,具有责任心,以追求卓越的科研成果为目标。对学生的本科毕业院校、专业背景没有要求,欢迎广大学子报考!

有意保送或报考的学生请先将个人简介发至我的邮箱neouma@mail.xidian.edu.cn!由于工作繁忙,不能一一回复邮件,我仅给我初选合格的学生回复邮件以确定进一步的报考事宜,望谅解!若一周内未收到我的回复邮件,请尽快报考其他导师!




专著

1. Jing Liu, Hussein A. Abbass, and Kay Chen Tan, Evolutionary Computation and Complex Networks, Springer, 2018.

2. David G. Green, Jing Liu, and Hussein A. Abbass, Dual Phase Evolution, Springer, 2013.

3. Licheng Jiao, Jing Liu, and Weicai Zhong, Coevolutionary Computation and Multiagent Systems, WIT, U. K., 2012.


国际期刊论文

1. Mingming Li, Jing Liu, Peng Wu, and Xiangyi Teng, Evolutionary network embedding preserving both local proximity and community structure, IEEE Trans. Evolutionary Computation, accept, 2019.

2. Peng Wu, Jing Liu, and Fang Shen, A deep one-class neural network for anomalous event detection in complex scenes, IEEE Trans. Neural Networks and Learning Systems, accept, 2019.

3. Xiangyi Teng, Jing Liu, and Mingming Li, Overlapping community detection in directed and undirected attributed networks using a multiobjective evolutionary algorithm, IEEE Trans. Cybernetics, accept, 2019.

4. Shuai Wang, Jing Liu, and Yaochu Jin, Finding influential nodes in multiplex networks using a memetic algorithm, IEEE Trans. Cybernetics, accept, 2019.

5. Luowen Liu and Jing Liu, Reconstructing gene regulatory networks via memetic algorithm and LASSO based on recurrent neural networks, Soft Computing, accept, 2019.

6. Ze Yang and Jing Liu, Learning fuzzy cognitive maps with convergence using a multi-agent genetic algorithm, Soft Computing, accept, 2019.

7. Yilan Wang and Jing Liu, A stable, unified density controlled memetic algorithm for gene regulatory networks reconstruction based on sparse fuzzy cognitive maps, Neural Processing Letters, accept, 2019.

8. Luowen Liu and Jing Liu, A sparse and decomposed particle swarm optimization for inferring gene regulatory networks based on fuzzy cognitive maps, Journal of Bioinformatics and Computational Biology, accept, 2019.

9. Yonglei Lu and Jing Liu, The impact of information dissemination strategies to epidemic spreading on complex networks, Physica A, accept, 2019.

10. Jing Liu, Yaxiong Chi, Zongdong Liu, and Shan He, An ensemble multi-objective evolutionary algorithm for gene regulatory network reconstruction based on fuzzy cognitive mapsCAAI Transactions on Intelligence Technology, accept, 2019.

11. Xingxing Hao, Jing Liu, Xiaoxiao Yuan, Xianglong Tang, and Zhangtao Li, A moving block sequence-based evolutionary algorithm for resource-constrained project scheduling problems, International Journal of Bio-Inspired Computation, accept, 2017.

12. Yaxiong Chi and Jing Liu, Reconstructing gene regulatory networks with a memetic-neural hybrid based on fuzzy cognitive maps, Natural Computing, accept, 2017.

13. Shuai Wang and Jing Liu, Constructing robust community structure against edge-based attacks, IEEE Systems Journal, 13(1): 582-592, 2019.

14. Shuai Wang and Jing Liu, Community robustness and its enhancement in interdependent networks, Applied Soft Computing, 77: 665-677, 2019.

15. Kai Wu, Jing Liu, and Dan Chen, Network reconstruction based on time series via memetic algorithm, Knowledge-Based Systems, 164: 404-425, 2019.

16. Shuai Wang and Jing Liu, Designing comprehensively robust networks against intentional attacks and cascading failures, Information Sciences, 478, 125-140, 2019.

17. Ze Yang and Jing Liu, Learning of fuzzy cognitive maps using a niching-based multi-modal multi-agent genetic algorithm, Applied Soft Computing, 74, 356-367, 2019.

18. Penghui Liu and Jing Liu, Good influence transmission structure strengthens cooperation in prisoner’s dilemma games, European Physical Journal B, 91: 321: 1-12, 2018.

19. Zhirou Yang and Jing Liu, A memetic algorithm for determining the nodal attacks with minimum cost on complex networks, Physica A, 503, 1041-1053, 2018.

20. Luowen Liu and Jing Liu, Inferring gene regulatory networks with hybrid of multi-agent genetic algorithm and random forests based on fuzzy cognitive maps, Applied Soft Computing, 69: 585-598, 2018.

21. Shanchao Yang and Jing Liu, Time series forecasting based on high-order fuzzy cognitive maps and wavelet transform, IEEE Trans. Fuzzy Systems, 26(6): 3391-3402, 2018.

22. Xiaodong Wang and Jing Liu, A comparative study of the measures for evaluating community structure in bipartite networks, Information Sciences, 448-449: 249-262, 2018.

23. Lei Rong and Jing Liu, A heuristic algorithm for enhancing the robustness of scale-free networks based on edge classification, Physica A, 503:503-515, 2018.

24. Mingming Li and Jing Liu, A link clustering based memetic algorithm for overlapping community detection, Physica A, , 503: 410-423, 2018.

25. Xumiao Zou and Jing Liu, A mutual information based two-phase memetic algorithm for large-scale fuzzy cognitive map learning, IEEE Trans. Fuzzy Systems, 26(4), pp. 2120-2134, 2018.

26. Zhangtao Li, Jing Liu, and Kai Wu, A multi-objective evolutionary algorithm based on structural and attribute similarities for community detection in attributed networks, IEEE Trans. Cybernetics, 48(7): 1963-1976, 2018.

27. Shuai Wang and Jing Liu, A multi-objective evolutionary algorithm for promoting the emergence of cooperation and controllable robustness on directed networks, IEEE Transactions on Network Science and Engineering, 5(2): 92-100, 2018.

28. Jie Yang and Jing Liu, Influence maximization-cost minimization in social networks based on a multiobjective discrete particle swarm optimization algorithm, IEEE Access, vol. 6, issue 1, pp. 2320-2329, 2018.

29. Zhirou Yang and Jing Liu, Robustness of scale-free networks with various parameters against cascading failures, Physica A, 492: 628-638, 2018.

30. Kai Wu, Jing Liu, Learning large-scale fuzzy cognitive maps based on compressed sensing and application in reconstructing gene regulatory networks, IEEE Trans. Fuzzy Systems, 25(6): 1546-1560, 2017.

31. Jing Liu, Yaxiong Chi, Chen Zhu, and Yaochu Jin, A time series driven decomposed evolutionary optimization approach for reconstructing large-scale gene regulatory networks based on fuzzy cognitive maps, BMC Bioinformatics, 18: 241, 2017.

32. Tao Zhang and Jing Liu, An efficient and fast kinematics-based algorithm for RFID network planning, Computer Networks, 121: 13-24, 2017.

33. Shuai Wang, Jing Liu, and Xiaodong Wang, Mitigation of attacks and errors on community structure in complex networks, Journal of Statistical Mechanics Theory and Experiment, 4, 043405, 2017.

34. Jing Liu, Mingxing Zhou, Shuai Wang, and Penghui Liu, A comparative study of network robustness measures,” Frontiers of Computer Science, 11(1): 1-17, 2017.

35. Penghui Liu and Jing Liu, Multi-leader PSO (MLPSO): a new PSO variant for solving global optimization problems, Applied Soft Computing, 61: 256-263, 2017.

36. Penghui Liu and Jing Liu, Multilevel evolutionary algorithm that optimizes the structure of scale-free networks for the promotion of cooperation in the prisoner’s dilemma game, Scientific Reports, 7, 4320, 2017.

37. Penghui Liu and Jing Liu, Contribution diversity and incremental learning promote cooperation in public goods games, Physica A, 486: 827-838, 2017.

38. Penghui Liu and Jing Liu, Robustness of coevolution in resolving prisoner’s dilemma games on interdependent networks subject to attack,” Physica A, 479: 362-370, 2017.

39. Yawen Zhou, Jing Liu, and Xiaohui Gan, A multi-objective evolutionary algorithm for multi-period dynamic emergency resource scheduling problems, Transportation Research Part E, 99: 77-95, 2017.

40. Mingxing Zhou and Jing Liu, A two-phase multi-objective evolutionary algorithm for enhancing the robustness of scale-free networks against multiple malicious attacks, IEEE Trans. Cybernetics, 47(2): 539-552, 2017.

41. Shuai Wang and Jing Liu, “Constructing robust cooperative networks using a multi-objective evolutionary algorithm,” Scientific Reports, 7, 41600, 2017.

42. Kai Wu, Jing Liu, and Yaxiong Chi, “Wavelet fuzzy cognitive maps,” Neurocomputing, 232: 94-103, 2017.

43. Penghui Liu and Jing Liu, Cooperation in the prisoner’s dilemma game on tunable community networks, Physica A, 472: 152-163, 2017.

44. Xiaodong Wang and Jing Liu, A layer reduction based community detection algorithm on multiplex networks, Physica A, 471: 244-252, 2017.

45. Jinhuang Huang, Jing Liu, and Xin Yao, A multi-agent evolutionary algorithm for software module clustering problems, Soft Computing, 21(12): 3415-3428, 2017.

46. Xingxing Hao and Jing Liu, A multiagent evolutionary algorithm with direct and indirect combined representation for constraint satisfaction problems, Soft Computing, 21(3): 781-793, 2017.

47. Mingxing Zhou, Jing Liu, Shuai Wang, and Shan He, A comparative study of robustness measures for cancer signaling networks, Big Data and Information Analytics, 2017, 2(1): 87-96.

48. Xiaoxiao Yuan, Jing Liu, Xingxing Hao, A moving block sequence-based evolutionary algorithm for resource investment project scheduling problems, Big Data and Information Analytics, 2017, 2(1): 39-58.

49. Xianglong Tang, Jing Liu, and XingxingHao, Mitigate cascading failures on networks using a memetic algorithm, Scientific Reports, 6, 38713, 2016.

50. Kai Wu, Jing Liu, and Shuai Wang, Reconstructing networks from profit sequences in evolutionary games via a multiobjective optimization approach with lasso initialization, Scientific Reports, 6, 37771, 2016.

51. Kai Wu and Jing Liu, Robust learning of large-scale fuzzy cognitive maps via the lasso from noisy time series, Knowledge-Based Systems, 113: 23-38, 2016.

52. Zhongzhou Jiang, Jing Liu, and Shuai Wang, Traveling salesman problems with PageRank distance on complex networks reveal community structure,” Physica A, 463: 293-302, 2016.

53. Shuai Wang and Jing Liu, The effect of link-based topological changes and recoveries on the robustness of cooperation on scale-free networks,” The European Physical Journal Plus, 131: 219, 2016.

54. Shuai Wang and Jing Liu, Robustness of single and interdependent scale-free interaction networks with various parameters, Physica A, 460: 139-151, 2016.

55. Boping Duan, Jing Liu, and Xianglong Tang, Optimizing the natural connectivity of Scale-free networks using simulated annealing, Physica A, 457: 192-201, 2016.

56. Liangliang Ma, Jing Liu, and Boping Duan, Evolution of network robustness under continuous topological changes, Physica A, 451: 623-631, 2016.

57. Jinhuang Huang and Jing Liu, A similarity-based modularization quality measure for software module clustering problems, Information Sciences, 342: 96-110, 2016.

58. Chenlong Liu, Jing Liu, and Zhongzhou Jiang, An improved multi-objective evolutionary algorithm for simultaneously detecting separated and overlapping communities, Natural Computing, 15(4): 635-651, 2016.

59. Jing Liu, Yaxiong Chi, and Chen Zhu, A dynamic multi-agent genetic algorithm for gene regulatory network reconstruction based on fuzzy cognitive maps,” IEEE Trans. Fuzzy Systems, 24(2): 419-431, 2016.

60. Yutong Zhang, Jing Liu, Mingxing Zhou, and Zhongzhou Jiang, A multi-objective memetic algorithm based on decomposition for big optimization problems, Memetic Computing, 8(1): 45-61, 2016.

61. Zhangtao Li and Jing Liu, A multi-agent genetic algorithm for community detection in complex networks, Physica A, 449: 336-347, 2016.

62. Boping Duan, Jing Liu, Mingxing Zhou, and Liangliang Ma, A comparative analysis of network robustness against different link attacks, Physica A, 448: 144-153, 2016.

63. Yaxiong Chi and Jing Liu, Learning of fuzzy cognitive maps with varying densities using a multi-objective evolutionary algorithm, IEEE Trans. Fuzzy Systems, 24(1): 71-81, 2016.

64. Xianglong Tang, Jing Liu, and Mingxing Zhou, Enhancing network robustness against targeted and random attacks using a memetic algorithm, EPL (Europhysics Letters), 111(3): 38005-p1-p6, 2015.

65. Liangliang Ma, Jing Liu, Boping Duan, and Mingxing Zhou, A theoretical estimation for the optimal network robustness measure R against malicious node attacks, EPL (Europhysics Letters), 111(2): 28003-p1-p5, 2015.

66. Mingxing Zhou and Jing Liu, A memetic algorithm for enhancing the robustness of scale-free networks against malicious attacks, Physica A, 410: 131-143, 2014.

67. Chenlong Liu, Jing Liu, and Zhongzhou Jiang, A multiobjective evolutionary algorithm based on similarity for community detection from signed social networks, IEEE Trans. Cybernetics, 44(12): 2274-2287, 2014.

68. Yadong Li, Jing Liu, and Chenlong Liu, A comparative analysis of evolutionary and memetic algorithms for community detection from signed social networks, Soft Computing, 18(2): 329-348, 2014.

69. Weicai Zhong, Jing Liu, and Li Zhang, Evolutionary dynamics of continuous strategy games on graphs and social networks under weak selection,” Biosystems, 111(2): 102-110, 2013.

70. Weiqi Chen, Jing Liu, and Shan He, Prior knowledge guided active modules identification: an integrated multi-objective approach, BMC Systems Biology, 2017.3.14, 11.

71. Xingxing Hao, Hui Zhao, and Jing Liu, Multifocus color image sequence fusion based on mean shift segmentation, Applied Optics, Vol. 54, No. 30, pp.8982-8989, 2015.

72. Jian Xiong, Jing Liu, Yingwu Chen, and Hussein A. Abbass, A knowledge-based evolutionary multi-objective approach for stochastic extended resource investment project scheduling problems, IEEE Trans. Evolutionary Computation, 18(5): 742-763, 2014.

73. Jing Liu, Hussein A. Abbass, David G. Green, and Weicai Zhong, Motif difficulty (MD): A predictive measure of problem difficulty for evolutionary algorithms using network motifs, Evolutionary Computation Journal (MIT), 2012, 20(3): 321-347.

74. Weicai Zhong and Jing Liu, Comments on ‘Scale-free networks without growth’, Physica A, 2012, 391: 2163-2165.

75. Jing Liu, Hussein A. Abbass, Weicai Zhong, and David G. Green, Local-global interaction and the emergence of scale-free networks with community structures, Artificial Life (MIT), 2011, 17(4): 263-279.

76. Jing Liu, Jinshu Li, Weicai Zhong, Li Zhang, and Ruochen Liu, “Minimum span frequency assignment based on a multiagent evolutionary algorithm,” International Journal of Swarm Intelligence Research, 2011, 2(3): 30-43.

77. Lam T. Bui, Jing Liu, Axel Bender, Michael Barlow, Slawomir Wesolkowski, and Hussein A. Abbass, DMEA: A direction-based multiobjective evolutionary algorithm, Memetic Computing, 2011, 3(4): 271-285.

78. Xue Li, Jing Liu, Quan Z. Sheng, Sherali Zeadally, and Weicai Zhong, TMS-RFID: temporal management of large-scale RFID applications, International Journal of Information Systems Frontiers, 2011, 13(4): 481-500.

79. Jing Liu, Weicai Zhong, and Licheng Jiao, A multiagent evolutionary algorithm for combinatorial optimization problems, IEEE Trans. on Systems, Man, and Cybernetics, Part B, 2010, 40(1): 229-240.

80. Jing Liu, Xue Li, and Weicai Zhong, Ambiguous decision trees for mining concept-drifting data streams, Pattern Recognition Letters, 2009, 30(15): 1347-1355.

81. Jing Liu, Weicai Zhong, Licheng Jiao, and Xue Li, Moving block sequence and organizational evolutionary algorithm for general floorplanning with arbitrarily shaped rectilinear blocks, IEEE Trans. Evolutionary Computation, 2008, 12(5): 630-646.

82. Jing Liu, Weicai Zhong, and Licheng Jiao, An organizational evolutionary algorithm for numerical optimization,” IEEE Trans. Systems, Man, and Cybernetics, Part B, 2007, 37(4): 1052-1064.

83. Jing Liu, Weicai Zhong, and Licheng Jiao, A multiagent evolutionary algorithm for constraint satisfaction problems, IEEE Trans. Systems, Man, and Cybernetics, Part B, 2006, 36(1): 54-73.

84. Licheng Jiao, Jing Liu, and Weicai Zhong, An organizational coevolutionary algorithm for classification, IEEE Trans. Evolutionary Computation, 2006, 10(1): 67-80.

85. Jing Liu, Weicai Zhong, and Licheng Jiao, Comments on ‘the 1993 DIMACS Graph Coloring Challenge’ and ‘Energy Function-Based Approaches to Graph Coloring’, IEEE Trans. Neural Networks, 2006, 17(2): 533.

86. Weicai Zhong, Jing Liu, Mengzhi Xue, and Licheng Jiao, A multiagent genetic algorithm for global numerical optimization, IEEE Trans. Systems, Man, and Cybernetics, Part B, 2004, 34(2): 1128-1141.

  • 教育经历Education Background
  • 工作经历Work Experience
  • 研究方向Research Focus
  • 社会兼职Social Affiliations
  • 智能计算
  • 复杂网络
  • 数据挖掘
  • 计算机视觉