个人简历

教育背景
2008/10–2013/07，英国布鲁内尔大学，信息科学、计算与数学学院，信息系统与计算研究专业，博士
2005/09–2008/07，中南大学，信息科学与控制学院，计算机应用专业，硕士
2000/09–2004/07，哈尔滨理工大学，计算机科学与技术学院，计算机科学与技术专业，学士
2000.9-2004.7 B.Sc. in Computer Science and Technology School of Computer Science and Technology, Harbin University of Science and Technology, China
2005.9-2008.7 M.Sc. in Computer Application Technology School of Information Science and Engineering, Central South University, China
2008.10-2013.4 Ph.D. in Information Systems and Computing School of Information Systems, Computing and Mathematics, Brunel University, UK
工作经历
2013/12 至今， 暨南大学，信息科学技术学院计算中心，讲师
2013/03–2013/11，英国阿伯丁大学，自然与计算科学学院，博士后
2005/02–2005/05，广东珠海市科亚信息技术有限公司，软件测试员
2013.12 to now Lecturer in Computer Science and Techonlogy College of Information Science and Technology, Jinan University, Guangzhou, China
2013.3-2013.11 Research Fellow in ‘Combinatorial Responses In Stress Signalling’ Project School of Natural and Computing Sciences, University of Aberdeen, UK
2005.2-2005.05 Software Tester CoreSolution Company, Zhuhai, Guangdong, China

研究领域

数据挖掘、人工智能、机器学习、系统生物学

近期论文

[1] D. Zhang, Y. Zhang, Z. Wu, and H. Du. Rank-Constrained Beamforming for MIMO Cognitive Interference Channel. Mobile Information Systems, Volume 2016 (2016) , 11 pages, Article ID 2152538, http://dx.doi.org/10.1155/2016/2152538 [SCI, EI]
[2] Z. Wu, W. Pang, and G. M. Coghill. An integrated qualitative and quantitative biochemical model learning framework using evolutionary strategy and simulated annealing. Cognitive Computation, December 2015, Volume 7, Issue 6, pp 637–651, DOI:10.1007/s12559-015-9328-x. (2015) [SCI, EI]
[3] Z. Wu, W. Pang, and G. M. Coghill. An integrative top-down and bottom-up qualitative model construction framework for exploration of biochemical systems. Soft Computing, 2015, 19:1595–1610, DOI 10.1007/s00500-014-1467-6. (2015) [SCI, EI]
[4] S. Rausanu, C. Grosan, Z. Wu, O. Parvu, R. Stoica, D. Gilbert. Computational models for inferring biochemical networks. Neural Computing and Applications, February 2015, Volume 26, Issue 2, pp 299-311, DOI: 10.1007/s00521-014-1617-x. (2015) (First online: 12 June 2014) [SCI, EI]
[5] Z. Wu, W. Pang, and G. M. Coghill. Stepwise modelling of biochemical pathways based on qualitative model learning. In Y. Jin and S. A. Thomas (eds), Proceeding of the 13th UK Workshop on Computational Intelligence. Computational Intelligence (UKCI 2013), 2013 13th UK Workshop on, Surrey, UK, 9-11 September. IEEE Xplore, pp. 31--37, IEEE Catalog Number CFP1348L-ART, ISBN 978-1-4799-1568-2. (2013) [EI]
[6] Z. Wu, C. Grosan, and D. Gilbert. Empirical study of computational intelligence strategies for biochemical systems modelling. The 6th International Workshop on Nature Inspired Cooperative Strategies for Optimization (NICSO 2013), 2-4, September, 2013, Canterbury, UK. In series of Studies in Computational Intelligence, DOI: 10.1007/978-3-319-01692-4_19, Springer, Volume 512, 2014, pp 245-260. (2013)
[7] S. Rausanu, C. Grosan, Z. Wu, O. Parvu and D. Gilbert. Evolving biochemical systems. IEEE Congress on Evolutionary Computation (CEC 2013), pp.1602-1609, DOI: 10.1109/CEC.2013.6557753. (2013) [EI]
[8] Z. Wu, S. Yang, and D. Gilbert. A Hybrid Approach to Piece-wise Modelling Biochemical Systems. In Proceedings of the 12th International Conference on Parallel Problem Solving From Nature (PPSN2012), Part I, LNCS 7491, pp. 519-528. Springer, Heidelberg. (2012) [EI]
[9] Z. Wu, Q. Gao, and D. Gilbert. Target driven biochemical network reconstruction based on petri nets and simulated annealing. In Proceedings of the 8th International Conference on Computational Methods in Systems Biology (CMSB2010), pp. 33-42, ACM, New York. (2010) [EI]