薛羽，教授， 博士生导师，IEEE 高级会员。主要研究方向为演化计算、深度学习、轻量化深度学习、轻量化大模型、计算机视觉、特征图选择等。主持国家自然科学基金面上项目2项，国家自然科学基金面上项目合作课题1项，国家自然科学基金青年科学基金项目1项、江苏省自然科学基金青年基金项目1项、江苏省高校自然科学研究项目1项目，其他省厅级项目4项；参与国家或省部级项目10余项。获中国自动化学会自然科学奖二等奖一项(序3)，获省自然科学奖三等奖一项(序2)。在国内外期刊发表学术论文100余篇，被引用次数逾8000次。连续多年入选全球前2%顶尖科学家。2篇第一作者论文入选全球影响力排名前1‰的ESI热点论文，另外有7篇第一作者论文入选全球影响力排名前1%的ESI高被引论文。20余篇合作论文入选全球影响力排名前1%的ESI高被引论文。担任《Memetic Computing》、《International Journal of Computing Science and Mathematics》等期刊副主编；《IEEE TETCI》、《Mathematics》、《Electronic Research Archive》等期刊客座编辑；为《IEEE TEVC》、《IEEE TNNLS》、《IEEE TETCI》、《IEEE TPAMI》、《IEEE TCYB》、《IEEE TKDE》、《IEEE Transactions on Systems, Man and Cybernetics Systems》、《IEEE Transactions on Automation Science and Engineering》、《IEEE Transactions on Fuzzy Systems》、《IEEE Transactions on Emerging Topics in Computing》、《IEEE Transactions on Green Communications and Networking》、《IEEE Transactions on Games》、《IEEE Transactions on Industrial Informatics》、《IEEE Transactions on Consumer Electronics》、《IEEE Transactions on Image Processing》、《SCIENCE CHINA Information Sciences》、《计算机学报》、《软件学报》、《计算机研究与发展》、《自动化学报》、《Swarm and Evolutionary Computation》、《Memetic Computing》、《Applied Soft Computing》、《Knowledge-Based Systems》、《International Journal of Machine Learning and Cybernetics》、《Information Sciences》、《European Journal of Operational Research》、《Complex & Intelligent Systems》、《Expert Systems With Applications》、《Pattern Recognition》、《Information Fusion》、《Engineering Applications of Artificial Intelligence》、《Journal of Visual Communication and Image Representation》、《Neural Networks》、《ACM Transactions on Evolutionary Learning and Optimization》、《International Journal of Pattern Recognition and Artificial Intelligence》、《NaturalComputing》、《Artificial Intelligence Review》、《Applied Intelligence》、《Frontiers of Computer Science》、《ArtificialIntelligenceReview》、《ACM Transactions on Management Information Systems》、《Machine Learning with Applications》、《IEEE Internet of Things Journal》等200多个SCI期刊的审稿人；主要承担《人工智能导论》(本科生)、《机器学习》(研究生和本科生、国际留学生)、《机器学习理论与应用》(国内博士生、国际留学博士生)等课程的教学工作。 

本人在人工智能（演化计算、深度学习、轻量化深度学习、轻量化大模型、计算机视觉、特征图选择）方向招收博士、硕士研究生(由于是博导，在软件学院和计算机学院/网络空间安全学院均可招生)。欢迎有远大理想、有坚强毅力、勤奋、好学、有上进心、能吃苦耐劳、有志研究人工智能理论、算法，开发人工智能产品的考生与我联系。欢迎真真正正想做点事情、心无杂念的同学和我联系，团队欲打造由一批精兵强将组成的队伍，怕苦怕累、分派任务推三阻四、拈轻怕重、没有担当、没有提升自我能力意愿的考生请千万不要和我联系。邮箱：xueyu@nuist.edu.cn；微信：xueyu1258; QQ: 66516797。

有推荐到萨里大学（QS2019年全球140，走国家留学基金联合资助渠道，相对容易, 课题组已有研三同学获得国家全额资助攻读萨里大学博士学位，国家公派、资助期4年，为其家庭节约大约人民币160万）、惠灵顿维多利亚大学（QS2022年全球194）、诺丁汉大学（QS全球前100）、东京大学（QS全球前25）、东京工业大学（QS全球前60）、日本理化学研究所、富山大学、南澳大学读博士的机会。

团队多名研究生获得研究生国家奖学金(2万元，直接发到学生卡上)、研究生校长奖学金(2万元，直接发到学生卡上)、研究生浦芯精英奖学金(1万元，直接发到学生卡上);多名硕博士获得二等博士学业奖学金（3.3万/年）、一等优秀硕士新生奖学金（3.2万/年）；多名硕士研究生获得一、二等学业奖学金（一等：1.8万/年；二等1.4万/年；三等0.8万/年）；多名研究生获得研究生科研与实践创新计划项目（学生项目，1.5万/项;2020年度江苏省研究生科研创新项目1项、2021年度江苏省研究生科研创新项目1项、2022年度江苏省研究生科研创新项目1项、2023年度江苏省研究生科研创新项目1项、2024年度江苏省研究生科研创新项目1项、2025年度江苏省研究生科研创新项目1项）。

课题组已有研究生在研三阶段成功获得国家留学基金委（CSC）全额资助前往英国萨里大学攻读博士学位，国家公派、资助期4年，为其家庭节约人民币约160万元。

所带研究生中，比较突出者，例如2022级韩小龙同学2024年度同时获得国家奖学金(20000元）+校长奖学金(20000元）+浦芯精英奖学金(10000元）+一等学业奖学金（18000元）+研究生科研与实践创新计划项目（15000元）=总计83000元奖励；另外，获得导师各类奖励和资助总计约59000元（论文专利奖励合计13000元+项目奖励3000元+助研费6000元+资助参加各类学术会议约22000元+文献出版费用约10000元+专利申请费用约5000元）。

培养学生情况：共培养博士生 7人（含毕业）；硕士生55人（含毕业）

所带学生均勤奋耐劳，无一人存在延迟毕业现象；所带学生研究方向为科技前沿，均能在秋招中提前找到高薪工作，研究生所掌握的先进技术均能直接用于解决公司企业面临的问题，直接负责公司项目上线运维工作。

优秀硕士毕业生去向：阿里巴巴蚂蚁金服（年薪70万）、微软（年薪40万）、宜兴市委办公室、南京市六合区发改委、中国移动、中国联通、中国电信、中国建设银行、南京信息工程大学、中国民生银行长沙分行、徐州电信、盐城师范学院、宣城市住建局、新奥新智科技有限公司、金陵机械制造总厂、白杨时代（南京）科技有限公司、江苏金陵科技集团有限公司、苏州农商行、中移（苏州）软件技术有限司、长安马自达、无锡祥生医疗科技股份有限公司等。

学术兼职：

(1) IEEE Transactions on Emerging Topics in Computational Intelligence客座编辑 (JCR 1区期刊;专刊题目：Neural Architecture Search and Large Machine Learning Models,  https://cis.ieee.org/publications/t-emerging-topics-in-ci/tetci-special-issues , Submission deadline: 31 December 2024)

(2) Mathematics客座编辑 (JCR 1区期刊;专刊题目：Evolutionary Computation for Feature Selection and Dimensionality Reduction,        https://www.mdpi.com/journal/mathematics/special_issues/64HV6EA39T  ,  Submission deadline: 10 Jun. 2025)

(3) Wireless Power Transfer 客座编辑 (专刊题目：Advanced Wireless Power Transmission Technology,  https://www.maxapress.com/wpt/specials/126  , Submission deadline: 1 July 2025)

(4) Electronic Research Archive客座编辑 (SCI 4区期刊;专刊题目：Evolutionary Generative Adversarial Networks for Different Industries and Applications, 网址：http://www.aimspress.com/era/article/6564/special-articles, 2023.08-2024.06)

(5) Mathematics客座编辑 (SCI 3区期刊;专刊题目：Evolutionary Computation for Deep Learning and Machine Learning, https://www.mdpi.com/journal/mathematics/special_issues/evolutionary_computation_deep_learning_machine_learning,  2023.08-2024.06, 第二期，第一期2023.01-2023.06)

(6) Neural Computing and Applications客座编辑 (SCI 2区期刊;专刊题目：Hybrid Approaches to Nature-inspired Optimization Algorithms and Their Applications, 网址：https://www.springer.com/journal/521/updates/23345646, 2023.01-2023.06)

(7) Frontiers in Plant Science客座编辑 (SCI 1区期刊;专刊题目：Intelligent Computing Research with Applications in Ecological Plant Protection, 网址： https://www.frontiersin.org/research-topics/46310/intelligent-computing-research-with-applications-in-biotechnology,  2023.01-2023.06)

(8) 2019年人工智能与安全国际会议Workshop（Evolutionary Computation for Deep Learning and Machine Learning）主席

(9) 2020年人工智能与安全国际会议Workshop（Evolutionary Computation for Deep Learning and Machine Learning）主席

(10) 2021年人工智能与安全国际会议Workshop（Evolutionary Computation for Deep Learning and Machine Learning）主席

(11) 2022年International Conference on Machine Learning, Cloud Computing and Intelligent Mining会议Workshop (Evolutionary Computation for Deep Learning and Machine Learning) 主席

(12) 中国仿真学会智能仿真优化与调度专委会委员、中国人工智能学会自然计算与数字智能城市专业委员会委员、中国人工智能学会人工智能与安全专业委员会委员、中国人工智能学会人工智能基础专业委员会委员、江苏省自动化学会智能优化与应用专委会等多个专业委员会委员

发表的部分学术论文：

[1]  Yu Xue, Jiajie Zha, Danilo Pelusi, Peng Chen, Tao Luo, Liangli Zhen, Yan Wang, and Mohamed Wahib, Neural architecture search with progressive evaluation and sub-population preservation, IEEE Transactions on Evolutionary Computation,DOI: 10.1109/TEVC.2024.3393304, 2024.

[2]  Yu Xue, Weinan Tong, Ferrante Neri, Peng Chen, Tao Luo, Liangli Zhen, and Xiao Wang, Evolutionary architecture search for generative adversarial networks based on weight sharing, IEEE Transactions on Evolutionary Computation, vol. 28, no. 3, pp. 653-667, 2024.

[3]  Yu Xue, Chen Chen, and Adam Slowik, Neural architecture search based on a multi-objective evolutionary algorithm with probability stack, IEEE Transactions on Evolutionary Computation, vol. 27, no. 4, pp. 778-786, 2023.

[4]  Yu Xue, Xiaolong Han, Ferrante Neri, Jiafeng Qin, and Danilo Pelusi, A gradient-guided evolutionary neural architecture search, IEEE Transactions on Neural Networks and Learning Systems,DOI：10.1109/TNLS.2024.3371432, pp. 1-13, 2024.

[5]  Pengcheng Jiang, Yu Xue, and Ferrante Neri, Score predictor-assisted evolutionary neural architecture search, IEEE Transactions on Emerging Topics in Computational Intelligence,DOI：10.1109/TETCI.2025.3526179, 2025.

[6]  Yu Xue, Changchang Lu, Ferrante Neri, and Jiafeng Qin, Improved differentiable architecture search with multi-stage progressive partial channel connections, IEEE Transactions on Emerging Topics in Computational Intelligence, vol. 8, no. 1, pp. 32-43, 2024.

[7]  Yu Xue, Xiaolong Han, and Zehong Wang, Self-adaptive weight based on dual-attention for differentiable neural architecture search, IEEE Transactions on Industrial Informatics, vol. 20, no. 4, pp. 6394-6403, 2024.

[8]  Yu Xue, Kun Chen, and Ferrante Neri, Differentiable architecture search with attention mechanisms for generative adversarial networks, IEEE Transactions on Emerging Topics in Computational Intelligence, vol. 8, no. 4, pp. 3141-3151, 2024.

[9]  Xu Cai, and Yu Xue, A population initialization method based on similarity and mutual information in evolutionary algorithm for bi-objective feature selection, ACM Transactions on Evolutionary Learning and Optimization, vol. 4, no. 3, pp. 1-21, 2024.

[10] Yu Xue, and Jiafeng Qin, Partial connection based on channel attention for differentiable neural architecture search, IEEE Transactions on Industrial Informatics, vol. 19, no. 5, pp. 6804-6813, 2023.

[11] Yu Xue, Yihang Tang, Xin Xu, Jiayu Liang, and Ferrante Neri, Multi-objective feature selection with missing data in classification, IEEE Transactions on Emerging Topics in Computational Intelligence, vol. 6, no. 2, pp. 355-364, 2022.

[12] Yu Xue, Xiangmao Chang, Shuiming Zhong, and Yi Zhuang, An efficient energy hole alleviating algorithm for wireless sensor networks, IEEE Transactions on Consumer Electronics, vol. 60, no. 3, pp. 347-355, 2014.

[13] Yu   Xue, Bing   Xue, and Mengjie Zhang, Self-adaptive particle swarm optimization for large-scale feature selection in classification, ACM Transactions on Knowledge Discovery from Data, vol. 13, no. 5, pp. 1-27, 2019.

[14] Chenyi Zhang, Yu Xue, Ferrante Neri, Xu Cai, and Adam Slowik, Multi-objective self-adaptive particle swarm optimization for large-scale feature selection in classification, International Journal of Neural Systems, vol. 34, no. 03, pp. 2450014, 2024.

[15] Yu Xue, and Anjing Zhu, An effective surrogate-assisted rank method for evolutionary neural architecture search, Applied Soft Computing, vol. 167, pp. 112392, 2024.

[16] Yu Xue, and Chenyi Zhang, A novel importance-guided particle swarm optimization based on MLP for solving large-scale feature selection problems, Swarm and Evolutionary Computation, vol. 91, pp. 101760, 2024.

[17] Yu Xue, Jiajie Zha, Mohamed Wahib, Tinghui Ouyang, and Xiao Wang, Neural architecture search via similarity adaptive guidance, Applied Soft Computing, vol. 162, pp. 111821, 2024.

[18] Xiaolong Han, Yu Xue, Zehong Wang, Yong Zhang, Anton Muravev, and Moncef Gabbouj, SaDENAS: a self-adaptive differential evolution algorithm for neural architecture search, Swarm and Evolutionary Computation, vol. 91, pp. 101736, 2024.

[19] 蒋鹏程, 薛羽, 基于排序得分预测的演化神经架构搜索方法, 计算机学报, vol. 47, no. 11, pp. 2522-2535, 2024.

[20] Yu Xue, Haokai Zhu, and Ferrante Neri, A feature selection approach based on NSGA-II with ReliefF, Applied Soft Computing, vol. 134, pp. 109987, 2023.

[21] Yu Xue, Yixia Zhang, and Ferrante Neri, A method based on evolutionary algorithms and channel attention mechanism to enhance cycle generative adversarial network performance for image translation, International Journal of Neural Systems, vol. 33, no. 05, pp. 2350026, 2023.

[22] Yu Xue, Qi Zhang, and Adam Slowik, Automatic topology optimization of echo state network based on particle swarm optimization, Engineering Applications of Artificial Intelligence, vol. 117, pp. 105574, 2023.

[23] Yu Xue, Chenyi Zhang, and Ferrante Neri, An external attention-based feature ranker for large-scale feature selection, Knowledge-Based Systems, vol. 281, pp. 111084, 2023.

[24] Pengcheng Jiang, Yu Xue, and Ferrante Neri, Continuously evolving dropout with multi-objective evolutionary optimisation, Engineering Applications of Artificial Intelligence, vol. 124, pp. 106504, 2023.

[25] Pengcheng Jiang, Yu Xue, and Ferrante Neri, Convolutional neural network pruning based on multi-objective feature map selection for image classification, Applied Soft Computing, vol. 139, pp. 110229, 2023.

[26] Yu Xue, Qi Zhang, and Yan Zhao, An improved brain storm optimization algorithm with new solution generation strategies for classification, Engineering Applications of Artificial Intelligence, vol. 110, pp. 104677, 2022.

[27] Yu Xue, Yiling Tong, and Ferrante Neri, An ensemble of differential evolution and Adam for training feed-forward neural networks, Information Sciences, vol. 608, pp. 453-471, 2022.

[28] Yu Xue, Xu Cai, and Ferrante Neri, A multi-objective evolutionary algorithm with interval based initialization and self-adaptive crossover operator for large-scale feature selection in classification, Applied Soft Computing, vol. 127, pp. 109420, 2022.

[29] Yu   Xue, Haokai   Zhu, Jiayu   Liang, and Adam Slowik, Adaptive crossover operator based multi-objective binary genetic algorithm for feature selection in classification, Knowledge-Based Systems, vol. 227, no. 5, pp. 1-9, 2021.

[30] Yu Xue, Qi Zhang, and Ferrante Neri, Self-adaptive particle swarm optimization-based echo state network for time series prediction, International Journal of Neural Systems, vol. 31, no. 12, pp. 1-15, 2021.

[31] Yu Xue, Yankang Wang, Jiayu Liang, and Adam Slowik, A self-adaptive mutation neural architecture search algorithm based on blocks, IEEE Computational Intelligence Magazine, vol. 16, no. 3, pp. 67-78, 2021.

[32] Yu Xue, Pengcheng Jiang, Ferrante Neri, and Jiayu Liang, A multi-objective evolutionary approach based on graph-in-graph for neural architecture search of convolutional neural networks, International Journal of Neural Systems, vol. 31, no. 09, pp. 2150035, 2021.

[33] Yu   Xue, Tao   Tang, Wei   Pang, and Alex X. Liu, Self-adaptive parameter and strategy based particle swarm optimization for large-scale feature selection problems with multiple classifiers, Applied Soft Computing, vol. 88, pp. 106031, 2020.

[34] 薛羽, 庄毅, 顾晶晶, 常相茂, 王洲, 自适应离散差分进化算法策略的选择, 软件学报, vol. 25, no. 5, pp. 984-996, 2014.

[35] 薛羽, 庄毅, 孟新, 张友益, 自适应学习集成优化算法及矩阵特征值求解, 计算机研究与发展, vol. 50, no. 7, pp. 1435-1443, 2013.

[36] Yixia Zhang, Yu Xue, and Ferrante Neri, Multi-optimiser training for GANs based on evolutionary computation, IEEE Congress on Evolutionary Computation (CEC), pp. 1-8, 2024.

[37] Yu Xue, Zhenman Zhang, and Ferrante Neri, Similarity surrogate-assisted evolutionary neural architecture search with dual encoding strategy, Electronic Research Archive, vol. 32, no. 2, pp. 1017-1043, 2024.

[38] Pengcheng Jiang, Yu Xue, Ferrante Neri, and Mohamed Wahib, Surrogate-assisted evolutionary neural architecture search with isomorphic training and prediction, International Conference on Intelligent Computing (ICIC), pp. 191-203, 2024.

[39] Liwen Jiang, Yu Xue, Ferrante Neri, Xiaoping Zhao, and Mohamed Wahib, Progressive neural predictor with score-based sampling, International Joint Conference on Neural Networks (IJCNN), pp. 1-8, 2024.

[40] 薛羽, 卢畅畅, 基于有偏采样的连续进化神经架构搜索, 计算机工程, vol. 50, no. 02, pp. 91-97, 2024.

[41] Zhenman Zhang, Yu Xue, and Adam Slowik, Sle-CNN: a novel convolutional neural network for sleep stage classification, Neural Computing and Applications, vol. 35, no. 23, pp. 17201-17216, 2023.

[42] Yu Xue, Yiling Tong, and Ferrante Neri, A hybrid training algorithm based on gradient descent and evolutionary computation, Applied Intelligence, vol. 53, no. 18, pp. 21465-21482, 2023.

[43] Yu Xue, Xu Cai, and Weiwei Jia, Particle swarm optimization based on filter-based population initialization method for feature selection in classification, Journal of Ambient Intelligence and Humanized Computing, vol. 14, no. 6, pp. 7355-7366, 2023.

[44] 薛羽, 张逸轩, 深层神经网络架构搜索综述, 信息网络安全, vol. 23, no. 09, pp. 58-74, 2023.

[45] 胡中源, 薛羽, and 查加杰, 演化循环神经网络研究综述, 计算机科学, vol. 50, no. 03, pp. 254-265, 2023.

[46] Yu Xue, Haokai Zhu, and Ferrante Neri, A self-adaptive multi-objective feature selection approach for classification problems, Integrated Computer-Aided Engineering, vol. 29, no. 1, pp. 3-21, 2022.

[47] Yu Xue, and Yan Zhao, Structure and weights search for classification with feature selection based on brain storm optimization algorithm, Applied Intelligence, vol. 52, no. 5, pp. 5857-5866, 2022.

[48] Yu Xue, Yankang Wang, and Jiayu Liang, A self-adaptive gradient descent search algorithm for fully-connected neural networks, Neurocomputing, vol. 478, pp. 70-80, 2022.

[49] Yu Xue, Weinan Tong, Ferrante Neri, and Yixia Zhang, PEGANs: phased evolutionary generative adversarial networks with self-attention module, Mathematics, vol. 10, no. 15, pp. 2792, 2022.

[50] Yu Xue, Bernard-Marie Onzo, Romany F Mansour, and Shoubao Su, Deep convolutional neural network approach for COVID-19 detection, Computer Systems Science & Engineering, vol. 42, no. 1, pp. 201-211, 2022.

[51] Yu Xue, Yan Zhao, and Adam Slowik, Classification based on brain storm optimization with feature selection, IEEE Access, vol. 9, pp. 16582 - 16590, 2021.

[52] Yu Xue, Yiling Tong, Ziming Yuan, Shoubao Su, Adam Slowik, and Sam Toglaw, Handwritten character recognition based on improved convolutional neural network, Intelligent Automation and Soft Computing, vol. 29, no. 2, pp. 497-509, 2021.

[53] Yu Xue, Jiafeng Qin, Shoubao Su, and Adam Slowik, Brain storm optimization based clustering for learning behavior analysis, Computer Systems Science and Engineering, vol. 39, no. 2, pp. 211-219, 2021.

[54] Yu Xue, Bernard-marie Onzo, and Ferrante Neri, Intrusion detection system based on an updated ANN model, Advances in Swarm Intelligence (ICSI ), pp. 472-479, 2021.

[55] Yu Xue, Chen Chen, Chishe Wang, Linguo Li, and Romany F. Mansour, Face image compression and reconstruction based on improved PCA, Intelligent Automation and Soft Computing, vol. 30, no. 3, pp. 973-982, 2021.

[56] Yu   Xue, Tao   Tang, and Alex X. Liu, Large-scale feedforward neural network optimization by a self-adaptive strategy and parameter based particle swarm optimization, IEEE Access, vol. 7, pp. 52473-52483, 2019.

[57] Yu Xue, Weiwei Jia, and Alex X Liu, A particle swarm optimization with filter-based population initialization for feature selection, IEEE Congress on Evolutionary Computation (CEC), pp. 1572-1579, 2019.

[58] Yu   Xue, Binping   Zhao, Tinghuai   Ma, and Alex X. Liu, An evolutionary classification method based on fireworks algorithm, International Journal of Bio-Inspired Computation, vol. 11, no. 3, pp. 149-158, 2018.

[59] Yu   Xue, Binping   Zhao, Tinghuai   Ma, and Wei Pang, A self-adaptive fireworks algorithm for classification problems, IEEE Access, vol. 6, no. 01, pp. 44406-44416, 2018.

[60] Yu   Xue, Jiongming   Jiang, Binping   Zhao, and Tinghuai Ma, A self-adaptive artificial bee colony algorithm based on global best for global optimization, Soft Computing, vol. 22, no. 9, pp. 2935-2952, 2018.

[61] Yu   Xue, Jiongming   Jiang, Tinghuai   Ma, Jingfa   Liu, and Wei Pang, A self-adaptive artificial bee colony algorithm with symmetry initialization, Journal of Internet Technology, vol. 19, no. 5, pp. 1347-1362, 2018.

[62] Yu   Xue, Weiwei   Jia, Xuejian   Zhao, and Wei Pang, An evolutionary computation based feature selection method for intrusion detection, Security and Communication Networks, vol. 2018, pp. 2492956, 2018.

[63] Jiongming   Jiang, Yu   Xue, Tinghuai   Ma, and Zhongyang Chen, Improved artificial bee colony algorithm with differential evolution for the numerical optimisation problems, International Journal of Computational Science and Engineering, vol. 16, no. 1, pp. 73-84, 2018.

[64] Yu   Xue, Jiongming   Jiang, Bing   Xue, and Mengjie Zhang, A classification method based on self-adaptive artificial bee colony, IEEE Symposium Series on Computational Intelligence (SSCI), pp. 1038–1045, 2017.

[65] Yu Xue, Binping Zhao, and Tinghuai Ma, Performance analysis for clustering algorithms, International Journal of Computing Science and Mathematics, vol. 7, no. 5, pp. 485-493, 2016.

[66] Yu   Xue, Binping   Zhao, and Tinghuai Ma, Classification based on fireworks algorithm, Bio-inspired Computing–Theories and Applications (BIC-TA), pp. 35-40, 2016.

[67] Yu   Xue, Tao   Tang, and Tinghuai Ma, Classification based on brain storm optimization algorithm, Bio-inspired Computing–Theories and Applications (BIC-TA), pp. 371-376, 2016.

[68] Yu Xue, Suiming Zhong, Tinghuai Ma, and Jie Cao, A hybrid evolutionary algorithm for numerical optimization problem, Intelligent Automation & Soft Computing, vol. 21, no. 4, pp. 473-490, 2015.

[69] Yu Xue, Yi Zhuang, Tianquan Ni, Siru Ni, and Xuezhi Wen, Self-adaptive learning based discrete differential evolution algorithm for solving CJWTA problem, Journal of Systems Engineering and Electronics, vol. 25, no. 1, pp. 59-68, 2014.

[70] Yu Xue, Shuiming Zhong, Yi Zhuang, and Bin Xu, An ensemble algorithm with self-adaptive learning techniques for high-dimensional numerical optimization, Applied Mathematics and Computation, vol. 231, pp. 329-346, 2014.

[71] 薛羽, 庄毅, 许斌, 张友益, 基于自适应学习群体搜索技术的集成进化算法, 系统工程理论与实践, vol. 34, no. 2, pp. 458-465, 2014.

[72] 薛羽, 庄毅, 朱浩, 张友益, 求解协同干扰问题的高效免疫遗传算法, 电子科技大学学报, vol. 42, no. 3, pp. 453-458, 2013.

[73] 薛羽, 庄毅, 张友益, 倪思如, and 赵学健, 基于启发式自适应离散差分进化算法的多 UCAV 协同干扰空战决策, 航空学报, vol. 34, no. 2, pp. 343-351, 2013.

[74] Yu Xue, Yi Zhuang, Tianquan Ni, Jian Ouyang, and Zhou Wang, Enhanced self-adaptive evolutionary algorithm for numerical optimization, Journal of Systems Engineering and Electronics, vol. 23, no. 6, pp. 921-928, 2012.

[75] Yu Xue, Yi Zhuang, Tianquan Ni, and Siru Ni, One improved genetic algorithm applied in the problem of dynamic jamming resource scheduling with multi-objective and multi-constraint, IEEE Fifth International Conference on Bio-Inspired Computing: Theories and Applications (BIC-TA), pp. 708-712, 2010.

获得授权的部分专利：

[1]朱陈陈，薛羽，基于多种群机制及代理模型的多目标演化神经架构搜索方法，2024-6-18，ZL 2024 1 0418128.3

[2]韩小龙，薛羽，田青，蒲勇霖，项正龙，王修来，基于差分进化算法的神经架构搜索方法和系统，2024-7-12，ZL 2024 1 0615399.8

[3]薛羽，陈京祥，费兰特·内里，田青，王修来，基于文本生成图像技术的文本视频检索优化方法，2024-8-16, ZL 2024 1 0802106.7

[4]胡博涵，薛羽，代理模型辅助的演化生成对抗网络架构搜索方法和系统，2024-11-29，ZL 2024 1 1300567.0

[5]陈坤，薛羽，一种基于注意力机制的扩散模型架构搜索方法和系统，2024-12-20，ZL 2024 1 1415408.5

[6]姚晨航，薛羽，一种基于可微分架构搜索的YOLO目标检测方法和系统，2025-1-24，ZL 2024 1 1601484.5

[7]张晓磊，薛羽，基于性能层级代理辅助的演化神经架构搜索方法和系统，2025-1-28，ZL 2024 1 1379555.1

[8]薛羽，王世超，王天宇，一种基于BSO改进的无人机通信组网方法，2020-6-5，ZL 2020 1 0503524.8

[9]蒋炯明，薛羽，一种基于改进ABC算法与DE变异策略的自适应聚类方法，2018-11-27，ZL 2015 1 0766519.5