深圳大学新葡的京集团350vip8888
College of Computer Science and Software Engineering, SZU
朱泽轩

智能技术与系统集成研究所副所长、人工智能系系主任 教授

智能技术与系统集成研究所

Email:zhuzx@szu.edu.cn

朱泽轩

      朱泽轩(博士,教授,博导)2003年获得复旦大学计算机科学与技术学士学位,2008年获得新加坡南洋理工大学计算机工程博士学位,2009-2010,在深圳大学新葡的京集团350vip8888但任讲师、2011年晋升副教授、2015年破格晋升教授,目前担任深圳大学新葡的京集团350vip8888人工智能系系主任、智能技术与系统集成研究所副所长。主要从事演化计算、机器学习、生物信息学等领域的研究工作。入选斯坦福全球前2%顶尖科学家榜单(World's Top 2% Scientists 2020, 2021),广东省首批特支计划创新青年拔尖人才,广东省首批高校优秀青年教师培养计划、深圳市首批“孔雀计划”海外高层次人才。担任中国数字音视频编解码技术标准工作组(AVS)基因压缩专题组组长,IEEE CIS, Emergent Technologies Task Force on Memetic Computing主席,期刊IEEE Transactions on Evolutionary Computation和IEEE Transactions on Emerging Topics in Computational Intelligence副主编。已主持国家重点研发计划课题2项、国家自然科学基金项目4项、省部级以上项目5项;在IEEE Transactions on Evolutionary Computation、IEEE Transactions on Cybernetics、IIEEE Transactions on Neural Networks and Learning Systems、Bioinformatics等期刊和国际会议发表论文150多篇,SCI他引2000多次。个人主页:http://csse.szu.edu.cn/staff/zhuzx

 

  • 代表论文
  •  

1.   S. Xie, T. He, S. He, and Z. Zhu*, CURC: A CUDA-based reference-free read compressor, Bioinformatics, 2022 (accepted)

2.   X. Ma, Z. Huang, X. Li, L. Wang, Y. Qi, and Z. Zhu*, Merged differential grouping for large-scale global optimization, IEEE Transactions on Evolutionary Computation, 2021 (accepted)

3.   X. Ma, Z. Huang, X. Li, Y. Qi, L. Wang, and Z. Zhu*, Multi-objectivization of single-objective optimization in evolutionary computation: A survey, IEEE Transactions on Cybernetics, 2021 (accepted)

4.   X. Ma, Y. Zheng, X. Li, L. Wang, Y. Qi, J. Yang and Z. Zhu*, Improving evolutionary multitasking optimization by leveraging inter-task gene similarity and mirror transformation, IEEE Computational Intelligence Magazine, 2021. (accepted)

5.   Z. Liang, X. Xu, L. Liu*, Y. Tu, and Z. Zhu*,Evolutionary many-task optimization based on multi-source knowledge transfer, IEEE Transactions on Evolutionary Computation, 2021 (accepted)

6.   Z. Liang, W. Liang, Z. Wang, X. Ma, L. Liu*, and Z. Zhu*, Multi-objective evolutionary multi-tasking with two-stage adaptive knowledge transfer based on population distribution, IEEE Transactions on Systems, Man, and Cybernetics - Systems, 2021 (accepted)

7.   X. Ma, J. Yin, A. Zhu, X. Li, Y. Yu, L. Wang, Y. Qi, and Z. Zhu*, Enhanced multifactorial evolutionary algorithm with meme helper-tasks, IEEE Transactions on Cybernetics, 2021. (accepted)

8.   Z. Liang, K. Hu, X. Ma, and Z. Zhu*, A many-objective evolutionary algorithm based on a two-round selection strategy, IEEE Transactions on Cybernetics, vol. 51, no. 3, pp. 1417-1429, 2021 (Code).

9.   Z.-A. Huang, J. Zhang, Z. Zhu*, E. Q. Wu, and K. C. Tan*, Identi?cation of autistic risk candidate genes and toxic chemicals via multi-label learning, IEEE Transactions on Neural Networks and Learning Systems, 2020, (accepted)

10. Z.-A. Huang, Z. Zhu*, C. Yau, and K. C. Tan*, Identifying autism spectrum disorder from resting-state fMRI using deep belief network, IEEE Transactions on Neural Networks and Learning Systems, 2020, (accepted)

11. Q. Lin, W. Lin, Z. Zhu*, M. Gong, J. Li, and C. A. Coello Coello, Multimodal multi-objective evolutionary optimization with dual clustering in decision and objective spaces, IEEE Transactions on Evolutionary Computation, 2020. (accepted)

12. X. Ma, Y. Yu, X. Li, Y. Qi, and Z. Zhu*, A survey of weight vector adjustment methods for decomposition based multi-objective evolutionary algorithms, IEEE Transactions on Evolutionary Computation, 2020. (accepted)

13. Z. Liang, H. Dong, C. Liu, W. Liang, and Z. Zhu*, Evolutionary multi-tasking for multi-objective optimization with subspace alignment and adaptive differential evolution, IEEE Transactions on Cybernetics, 2020. (accepted, Code)

14. Z. Liang, T. Wu, X. Ma, Z. Zhu*, and S. Yang, A dynamic multi-objective evolutionary algorithm based on decision variable classification, IEEE Transactions on Cybernetics, 2020. (accepted, Code)

15. Z. Liang, T. Luo, K. Hu, X. Ma, and Z. Zhu*, An indicator-based many-objective evolutionary algorithm with boundary protection, IEEE Transactions on Cybernetics, 2019. (accepted,Code)

16. X. Ma, X. Li, Q. Zhang, K. Tang, Z. Liang, W. Xie, and Z. Zhu*, A survey on cooperative co-evolutionary algorithms, IEEE Transactions on Evolutionary Computation, vol. 23, no. 3, pp. 421-441, 2019.

17. R. Guo, Y.-R. Li, S. He, L. Ou-Yang, Y. Sun*, and Z. Zhu*, RepLong - de novo repeat identification using long read sequencing data, Bioinformatics, vol. 34, no. 7, pp. 1099-1107, 2018. (Code)

18. X. Ma, Q. Zhang, G. Tian, J. Yang, and Z. Zhu*, On Tchebycheff decomposition approaches for multi-objective evolutionary optimization, IEEE Transactions on Evolutionary Computation, vol. 22, no. 2, pp. 226-244, 2018. (Code)

19. Z.-H, You, Z.-A. Huang, Z. Zhu*, G.-Y. Yan, Z.-W. Li, Z. Wen, and X. Chen*, PBMDA: A novel and effective path-based computational model for miRNA-disease association prediction, PLoS Computational Biology, vol. 13, no. 3, artical no. e1005455, 2017.(Code and Datasets)

20. Z.-A. Huang, Z. Wen, Q. Deng, Y. Chu, Y. Sun, and Z. Zhu*,LW-FQZip 2: a parallelized reference-based compression of FASTQ files, BMC Bioinformatics, vol. 18, no. 1, pp. 179:1-179:8, 2017.(Code)

21. Z. Zhu, L. Li, Y. Zhang, Y. Yang, and X. Yang, CompMap: a reference-based compression program to speed up read mapping to related reference sequences, Bioinformatics, vol. 31, no. 3, pp. 426-428, 2015.(Code)

22. Z. Zhu, Y. Zhang, Z. Ji, S. He, and X. Yang, High-throughput DNA sequence data compression, Briefings in Bioinformatics, vol. 16, no. 1, pp. 1-15, 2015.

23. Y. Zhang, L. Li, Y. Yang, X. Yang, S. He and Z. Zhu*, Light-weight reference-based compression of FASTQ data, BMC Bioinformatics, vol. 16, pp.188, 2015.(Code)

24. Z. Zhu, J. Zhou, Z. Ji, and Y.-H. Shi, DNA sequence compression using adaptive particle swarm optimization-based memetic algorithm, IEEE Transactions on Evolutionary Computation, vol. 15, no. 5, pp. 643-558, 2011.

25. Z. Zhu, S. Jia, and Z. Ji, Towards a memetic feature selection paradigm, IEEE Computational Intelligence Magazine, vol. 5, no. 2, pp. 41-53, 2010.

26. Z. Zhu, Y. S. Ong and M. Zurada, Identification of full and partial class relevant genes, IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 7, no. 2, pp. 263-277, 2010.(Datasets)

27. Z. Zhu, Y. S. Ong and M. Dash, Markov blanket-embedded genetic algorithm for gene selection, Pattern Recognition, vol. 49, no. 11, pp. 3236-3248, 2007.(DatasetsCode)

28. Z. Zhu, Y. S. Ong and M. Dash, Wrapper-filter feature selection algorithm using a memetic framework, IEEE Transactions On Systems, Man and Cybernetics - Part B:Cybernetics,  vol. 37, no. 1, pp. 70-76, 2007.(Code)

 

 

  • 主持主要项目
  •  

1. 国家自然科学基金面上项目: 基于自组装参考基因组的高通量长读测序数据压缩和比对集成研究,2019-2022

2. 国家自然科学基金面上项目:基于高通量RNA-Seq和多目标协同演化模因计算的疾病模块识别研究,2015-2018

3. 国家自然科学基金委与英国皇家学会中英联合项目: 基于计算智能技术的集成生物标记识别研究, 2012-2014

4. 国家自然科学基金青年基金项目:基于自生式多目标Memetic算法的高维数据特征选择研究,2011-2013

5. 教育部回国留学人员启动基金项目:晶体结构预测中的Memetic算法研究,2012-2013

6. 广东省特支计划创新青年拔尖人才项目,2015-2018

7. 广东省高等学校优秀青年教师培养计划资助项目:基于多组学大数据的智能生物标志物识别研究, 2014-2016

XML 地图