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；生物信息学
朱泽轩，博士，教授，博导。深圳大学人工智能学院副院长、大数据系统计算技术国家工程实验室副主任。
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，目前担任深圳大学人工智能学院副院长、大数据系统计算技术国家工程实验室副主任。主要从事计算智能、生物信息学等领域的研究工作。近五年连续入选斯坦福全球前2%顶尖科学家榜单，入选广东省特支计划珠江学者特聘教授和创新青年拔尖人才，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/曾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5项，以第一/通讯作者在Nature子刊、IEEE Transactions等重要期刊和国际会议发表论文多篇，GS引用10000多次，获得广东省科技进步一等奖（序2）、广东省人工智能产业协会自然科学一等奖（序1）。
个人主页：http://csse.szu.edu.cn/staff/zhuzx
L. Qin, X. Yang, X. Xu, and Z. Zhu*, A survey of deep learning in histopathological nuclear segmentation, IEEE Computational Intelligence Magazine, vol. 20, no. 3, pp. 19-40, 2025
J. Ji, H. Jin, J. Zhao, Q. Lin, J. Li, and Z. Zhu*, A logic circuit-based intrusion detection system using a dendritic neural model ensemble, IEEE Computational Intelligence Magazine, vol. 20, no. 2, pp. 20-32, 2025.
J. Cao, J. Zhang, Q. Yu, J. Ji, J. Li, S. He, and Z. Zhu*,TG-CDDPM: Text-guided antimicrobial peptides generation based on conditional denoising diffusion probabilistic model, Briefings in Bioinformatics, vol. 26, no. 1, article no. bbae644, 2025.
Y. Yue, S. Li, Y. Cheng, L. Wang, T. Hou, Z. Zhu*, and S. He*, Integration of molecular coarse-grained model into geometric representation learning framework for protein-protein complex property prediction, Nature Communications, vol. 15, article no. 9629, 2024.
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, vol. 15, article no. 3126, 2024.
Z. Liu, J. Yuan, H. Zhang, T. Zeng, and Z. Zhu*, Optimal linear crossover for mitigating negative transfer in evolutionary multitasking, IEEE Transactions on Evolutionary Computation, 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, vol. 29, no. 3, pp. 676-696, 2025.
X. Luo, Y. Chen, L. Liu, L. Ding, Y. Li, S. Li, Y. Zhang*, and Z. Zhu*, GSC: Efficient lossless compression of VCF files with fast query, GigaScience，vol. 13, article no. giae046, 2024.
T. Dai, M. Ya, J. Li, X. Zhang, S.-T. Xia, and Z. Zhu*, CFGN: A lightweight context feature guided network for image super-resolution, IEEE Transactions on Emerging Topics in Computational Intelligence, vol. 8, no. 1, pp. 855-865, 2024.
Z. Liu, G. Li, H. Zhang, Z. Liang, and Z. Zhu*, Multifactorial evolutionary algorithm based on diffusion gradient descent, IEEE Transactions on Cybernetics, vol. 54, no. 7, pp. 4267-4279, 2024.
L. Liu, W. Yuan, Z. Liang, X. Ma, and Z. Zhu*, Construction of polar codes based on memetic algorithm, IEEE Transactions on Emerging Topics in Computational Intelligence, vol. 7, no. 5, pp. 1539-1553, 2023
M. Yang, Z.-A Huang, W. Zhou, J. Ji, J. Zhang, S. He, and Z. 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, and Z. 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, and Z. 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, and Z. 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*, and Z. 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, and Z. 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*, and Z. 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, and Z. 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, and Z. 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.
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.
Z. Liang, X. Xu, L. Liu*, Y. Tu, and Z. 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 and Z. 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, and Z. Zhu*, An indicator-based many-objective evolutionary algorithm with boundary protection, IEEE Transactions on Cybernetics, vol. 51, no. 9, pp. 4553-2566, 2021.
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.
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, and Z. 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, and Z. 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*, and Z. Zhu*, RepLong - de novo repeat identification using long read sequencing data, Bioinformatics, vol. 34, no. 7, pp. 1099-1107, 2018.
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.
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.
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.
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.
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 and Z. Zhu*, Light-weight reference-based compression of FASTQ data, BMC Bioinformatics, vol. 16, pp.188, 2015.
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.
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.
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.
国家自然科学基金面上项目: 基于纳米孔测序的DNA存储关键信息技术研究，2025-2028
国家重点研发计划课题: DNA 存储实时编解码关键技术研发，2022-2025
国家重点研发计划"国际合作"重点专项课题: 高通量基因组数据智能高效压缩与传输及自主国家标准制定，2020-2022
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
