联系方式：zhuzx@szu.edu.cn

招生专业：计算机科学与技术(081200)

招生方向：人工智能

朱泽轩，博士，教授，博导。深圳大学大数据系统计算技术国家工程实验室副主任、计算机与软件学院人工智能系系主任、智能技术与系统集成研究所副所长。

个人简介：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，在深圳大学计算机与软件学院但任讲师、2011年晋升副教授、2015年破格晋升教授。目前担任深圳大学大数据系统计算技术国家工程实验室副主任、计算机与软件学院人工智能系系主任、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 2020-2022)，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 Computational Intelligence Society, 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，在Nature Communications、EEE Transactions on Evolutionary Computation、IEEE Transactions on Cybernetics、Briefings in Bioinformatics、Bioinformatics等期刊和国际会议发表论文多篇，GS引用7000多次。

个人主页：http://csse.szu.edu.cn/staff/zhuzx

代表论文

Q. Zhou, F. Ji, D. Lin, X. Liu,Z. Zhu*, and J. Ruan*, KSNP: a fast DBG-based haplotyping tool approaching data-in time cost,Nature Communications, 2024.(accepted)

Q. Yu, Q. Lin, J. Ji, W. Zhou, S. He,Z. Zhu*, and K. C. Tan, A survey on evolutionary computation based drug discovery,IEEE Transactions on Evolutionary Computation，2024（accepted）

T. Dai, M. Ya, J. Li, X. Zhang, S.-T. Xia, andZ. Zhu*,CFGN: A lightweight context feature guided network for image super-resolution,IEEE Transactions on Emerging Topics in Computational Intelligence,2023 (accepted)

Z. Liu, G. Li, H. Zhang, Z. Liang, andZ. Zhu*,Multifactorial evolutionary algorithm based on diffusion gradient descent,IEEE Transactions on Cybernetics, 2023 (accepted)

L. Liu, W. Yuan, Z. Liang, X. Ma, andZ. Zhu*, Construction of polar codes based on memetic algorithm,IEEE Transactions on Emerging Topics in Computational Intelligence,2022 (accepted)

M. Yang, Z.-A Huang, W. Zhou, J. Ji, J. Zhang, S. He, andZ. Zhu*, MIX-TPI: A flexible prediction framework for TCR-pMHC interactions based on multimodal representations,Bioinformatics, vol. 39, no. 8, Article no. btad475, 2023.

Z. Liang, Y. Zhu, X. Wang, Z. Li, andZ. Zhu*，Evolutionary multitasking for multi-objective optimization based on generative strategies,IEEE Transactions on Evolutionary Computation, vol. 27, no. 4, pp. 1042-1056, 2023.

X. Ma, Z. Huang, X. Li, Y. Qi, L. Wang, andZ. Zhu*,Multiobjectivization of single-objective optimization in evolutionary computation: A survey,IEEE Transactions on Cybernetics, vol. 53, no. 6, pp. 3702-2715, 2023.

X. Ma, Z. Huang, X. Li, L. Wang, Y. Qi, andZ. Zhu*, Merged differential grouping for large-scale global optimization,IEEE Transactions on Evolutionary Computation, vol. 26, no. 6, pp. 1439-1451, 2022.

M. Yang, Z.-A Huang, W. Gu, K. Han, W. Pan, X. Yang*, andZ. Zhu*, Prediction of biomarker-disease associations based on graph attention network and text representation,Briefings in Bioinformatics, vol. 23, no. 5, pp. 1-14, 2022

S. Xie, T. He, S. He, andZ. Zhu*, CURC: A CUDA-based reference-free read compressor,Bioinformatics, vol. 38, no. 12, pp. 3294-3296, 2022.

Z. Liang, W. Liang, Z. Wang, X. Ma, L. Liu*, andZ. Zhu*, Multiobjective evolutionary multitasking with two-stage adaptive knowledge transfer based on population distribution,IEEE Transactions on Systems, Man, and Cybernetics - Systems, vol. 52, no. 7, pp. 4457-4469, 2022.

X. Ma, J. Yin, A. Zhu, X. Li, Y. Yu, L. Wang, Y. Qi, andZ. Zhu*,Enhanced multifactorial evolutionary algorithm with meme helper-tasks,IEEE Transactions on Cybernetics, vol. 52, no. 8, pp. 7837-7851, 2022.

Z. Liang, H. Dong, C. Liu, W. Liang, andZ. Zhu*, Evolutionary multitasking for multiobjective optimization with subspace alignment and adaptive differential evolution,IEEE Transactions on Cybernetics, vol. 52, no. 4, pp. 2096-2109, 2022. (Code)

Z. Liang, T. Wu, X. Ma,Z. Zhu*, and S. Yang, A dynamic multiobjective evolutionary algorithm based on decision variable classification,IEEE Transactions on Cybernetics, vol. 52, no. 3, pp. 1602-1615, 2022. (Code)

Z. Liang, X. Xu, L. Liu*, Y. Tu, andZ. Zhu*，Evolutionary many-task optimization based on multisource knowledge transfer,IEEE Transactions on Evolutionary Computation, vol. 26, no. 2, pp. 319-333, 2022.

X. Ma, Y. Zheng, X. Li, L. Wang, Y. Qi, J. Yang andZ. Zhu*,Improving evolutionary multitasking optimization by leveraging inter-task gene similarity and mirror transformation,IEEE Computational Intelligence Magazine, vol. 16, no. 4, pp.38-51, 2021.

Z. Liang, T. Luo, K. Hu, X. Ma, andZ. Zhu*, An indicator-based many-objective evolutionary algorithm with boundary protection,IEEE Transactions on Cybernetics, vol. 51, no. 9, pp. 4553-2566, 2021. (Code)

Z. Liang, K. Hu, X. Ma, andZ. 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).

Z.-A. Huang, J. Zhang,Z. Zhu*, E. Q. Wu, and K. C. Tan*, Identification of autistic risk candidate genes and toxic chemicals via multi-label learning,IEEE Transactions on Neural Networks and Learning Systems, vol. 32, no. 9, pp. 3971-3984, 2021.

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, vol. 32, no. 7, pp. 2847-2861, 2021.

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, vol. 25, no. 1, pp. 130-144, 2021.

X. Ma, Y. Yu, X. Li, Y. Qi, andZ. Zhu*, A survey of weight vector adjustment methods for decomposition based multi-objective evolutionary algorithms,IEEE Transactions on Evolutionary Computation, vol.‏24, no.4, pp. 634-649, 2020

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

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

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

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)

Z.-A. Huang, Z. Wen, Q. Deng, Y. Chu, Y. Sun, andZ. 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)

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)

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.

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

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.

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.

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)

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.(Datasets,Code)

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

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

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

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

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

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

广东省特支计划创新青年拔尖人才项目，2015-2018

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