慕彩红，西安电子科技大学人工智能学院教授，博士生导师，智能感知与图像理解教育部重点实验室成员，智能感知与计算国际联合研究中心成员，国家“111”计划创新引智基地成员，美国电气电子工程师协会(IEEE)高级会员。目前担任Applied Soft Computing、PLOS One等国际期刊的编委，以及ACM Computing Surveys，Knowledge-Based Systems等国际期刊的审稿人。研究方向为计算智能、机器学习、遥感图像处理和推荐系统等。主持国家自然科学基金项目3项。发表学术论文50余篇，获授权国家发明专利30余项。

 纵向科研方面，作为主持人已完成国家自然科学基金青年基金项目“结合免疫和拉马克机制的协同进化模型及其应用研究”（61003199，2011年1月至2013年12月，19万）、国家自然科学基金面上项目“个性化推荐系统中基于协同进化学习的信息核优化与分析”（61672405，2017年1月至2020年12月，63万），国家自然科学基金面上项目“面向个性化辅助学习跨域推荐的演化图神经网络”（62077038，2021年1月至2024年12月，48万）。横向科研方面，近几年先后参与了“目标识别系统及隐身目标数字模型采购”（19.8万），“某轨迹规划与协同策略研究”（50万）等相关科研项目。

 教学方面，参与建设的《人工智能导论》课程2021年获批省级一流本科课程系列之线上一流课程，2023年获批国家级一流线上本科课程。作为主要成员，编著出版了教材《简明人工智能》和《人工智能导论》，以及教育部“101计划”核心教材《智能计算模型与理论》。目前承担《人工智能导论》课程的本科教学工作和《计算智能算法及应用》课程的研究生教学工作。获得西安电子科技大学2021年度本科优质教学奖二等奖，第二届西安电子科技大学“微课”教学比赛二等奖。

 研究生培养方面，累计培养硕士研究生41人，目前指导在读硕士研究生和博士研究生10余人。团队成员多人次获得国家级或省级竞赛奖项、国家奖学金、西安电子科技大学年度优秀研究生和西安电子科技大学优秀研究生干部等称号。

学术工作经历：

•   2004/03－2006/06，西安电子科技大学，助教

•   2006/06－2011/06，西安电子科技大学，讲师

•   2011/06－2020/07，西安电子科技大学，副教授

•   2020/07－今，         西安电子科技大学，教授

•   2016/12-2017/12，英国诺丁汉大学，计算机科学学院，访问学者

2026年研究生招生计划：

硕士生：2-3人。

博士生：2人。

课题组学术论文：

[70] Xiangrong Yan, Caihong Mu, Yi Liu*. DPGC: Adversarial Domain Adaptive Network Based on Dynamic Class Prototype and Graph Convolution for Few-Shot Hyperspectral Image Classification[C]. 28th European Conference on Artificial Intelligence (ECAI), Bologna, Italy, Oct. 25-30, 2025. (CCF推荐B类会议)

[69] Yi Liu, Jiajie Feng, Caihong Mu*, Xinyu He. Subpixel attention and frequency-domain cross modulation network for multimodal remote sensing image classification[J]. Applied Soft Computing, 2026, 186: 114073.

[68] Jing Liu*, Lina Lian, Yuanyuan Li, Yi Liu. Hyperspectral Image Classification Based on Fractional Fourier Transform[J]. Remote Sensing, 2025, 17(12): 2065.

[67] Jing Liu*, Meiyi Wu, KangXin Li, Yi Liu. A Lightweight Network Based on Dynamic Split Pointwise Convolution Strategy for Hyperspectral Remote Sensing Images Classification[J]. Remote Sensing, 2025, 17(5): 888.

[66] Caihong Mu, Zeyu Zhang, Yafeng Wang, Suling Chen, Yi Liu*. Masked self-supervised dual-scale transformer for enhanced hyperspectral image classification[J]. The Visual Computer, 2025, 41(14): 12145–12164. (CCF推荐C类期刊)

[65] Caihong Mu, Yu Liu, Zhidong Dong, Jiajie Feng, Yi Liu*. Semi-supervised learning combined with regression pre-training of Siamese network based on superpixel segmentation for hyperspectral image classification[J]. Machine Vision and Applications, 2025, 36(6): 126. (CCF推荐C类期刊)

[64] Mosa Haidarh, Caihong Mu, Yi Liu*. Hybrid multiscale spectral-spatial swin transformer for hyperspectral image classification[J]. Optics and Laser Technology, 2025, 192: 113923.

[63] Lang Qin, Yi Liu, Caihong Mu*. A social recommendation model based on social semantic mining and denoising[J]. Journal of Information and Intelligence, 2025, 3(4): 361–374.

[62] Caihong Mu, Fugui Zhang, Jiajie Feng, Mosa Haidarh, Yi Liu*. GhostNet and pair-wise similarity module for cross-domain few-shot classification of hyperspectral images[J]. Applied Soft Computing, 2025, 183: 113717.

[61] Yu Liu, Caihong Mu, Yi Liu*, Yafeng Wang. Multi-task Learning Based on Dense Feature Pyramid Network and Multi-scale Attention for Class-Imbalanced Hyperspectral Image Classification[C]. 21st International Conference on Intelligent Computing (ICIC), Ningbo, China, July 26-29, 2025. (CCF推荐C类会议)

[60] Yafeng Wang, Yi Liu, Caihong Mu*. UNet-PRFN: A Lightweight Network Based on 3D U-Net for Few-Shot Hyperspectral Image Classification[C]. 21st International Conference on Intelligent Computing (ICIC), Ningbo, China, July 26-29, 2025. (CCF推荐C类会议)

[59] Bokun Ma, Caihong Mu, Yi Liu*, Xinyu He, Mosa Haidarh. RoSENet: Rotation and Similarity Enhancement Network for Multimodal Remote Sensing Image Land Cover Classification[J]. IEEE Transactions on Geoscience and Remote Sensing, 63: 5511318, 2025.

(Full paper: https://doi.org/10.1109/TGRS.2025.3561850 )

(Code: https://github.com/mabokun618/RoSENet )

[58] Caihong Mu, Yunfei Fang, Jialiang Zhou, Yi Liu*. Enhancing Embeddings Quality with Stacked Gate for Click-Through Rate Prediction[C]. 24th IEEE International Conference on Data Mining (ICDM), Abu Dhabi, United Arab Emirates, Dec. 9-12, 2024. (录取为长文Regular Paper, CCF推荐B类会议, CORE Rank: A*, 长文录取率当年为10%左右)

[57] Caihong Mu, Haikun Yu, Lang Qin, Yi Liu*. Dual‑view data augmentation at subgraph level and graph contrastive learning for sequential recommendation[J]. Machine Learning, 2025, 114: 62. (CCF推荐B类期刊) (2025年2月)

[56] Yu Liu, Caihong Mu, Shanjiao Jiang, Yi Liu*. Unsupervised meta-learning with domain adaptation based on a multi-task reconstruction-classification network for few-shot hyperspectral image classification[J]. Journal of Information and Intelligence, 2025, 3(2): 103-112. (2025年3月)

[55] Mosa Haidarh, Caihong Mu, Yi Liu*. A Hybrid CNN-Swin Transformer Module for Hyperspectral Image Classification[C]. 12th International Conference on Information Systems and Computing Technology (ISCTech), Xi'an, China, Nov. 8-11, 2024, pp. 1-5. (2025年1月)

[54] Caihong Mu, Keyang Zhang, Jialiang Zhou, Yi Liu*. Perturbation-driven Dual Auxiliary Contrastive Learning for Collaborative Filtering Recommendation[C]. 31st International Conference on Computational Linguistics (COLING), Abu Dhabi, UAE, Jan. 19-24, 2025, pp. 647-657. (CCF推荐B类会议, CORE Rank: B) (2025年1月)

[53] 慕彩红, 张富贵, 闫香蓉, 刘逸*. 子空间与存储体的高光谱图像跨域小样本分类[J]. 西安电子科技大学学报, 2024, 51(5): 82-96. (2024年10月)

[52] Caihong Mu, Jiahuan Chen, Yunlong Chen, Yi Liu*. Multi-interest Awareness Model for Session-based Recommendation[C]. 2024 IEEE International Conference on Web Services (ICWS), Shenzhen, China, Jul. 7-13, 2024, pp. 1350-1352. (CCF推荐B类会议, CORE Rank: A) (2024年10月)

[51] Caihong Mu, Keyang Zhang, Jiashen Luo, Yi Liu*. PGCF: Perception graph collaborative filtering for recommendation[J]. Journal of Information and Intelligence, 2024, 2(6): 525-534. (2024年11月)

[50] Aamir Ali, Caihong Mu, Yafeng Wang, Yi Liu*. L-MFFN: Lightweight Multiscale Feature Fusion Network with Limited Samples for HSI Classification[C]. 2024 9th International Conference on Signal and Image Processing (ICSIP), Nanjing, China, Jul. 12-14, 2024, pp. 569-574. (西安电子科技大学高水平国际会议目录T2) (2024年9月)

[49] Yujie Yan, Yi Liu*, Yafeng Wang, Caihong Mu. A Multi-Attention Network with Multi-Level Spatial-Spectral Feature Fusion Based on Band Selection for Hyperspectral Image Classification[C]. 2024 International Joint Conference on Neural Networks (IJCNN), Yokohama, Japan, Jun. 30 - Jul. 5, 2024, pp. 1-7. (CCF推荐C类会议, CORE Rank: B) (2024年9月)

[48] Yi Liu, Shanjiao Jiang, Yijin Liu, Caihong Mu*. Spatial Feature Enhancement and Attention-Guided Bidirectional Sequential Spectral Feature Extraction for Hyperspectral Image Classification[J]. Remote Sensing, 16(17): 3124, 2024.

[47] Caihong Mu, Yu Liu, Xiangrong Yan, Aamir Ali, Yi Liu*. Few-Shot Open-Set Hyperspectral Image Classification With Adaptive Threshold Using Self-Supervised Multitask Learning[J]. IEEE Transactions on Geoscience and Remote Sensing, 62: 5526618, 2024.

( Full paper: https://doi.org/10.1109/TGRS.2024.3441617  )

( Code: https://github.com/yuliu213/SSMTL  )

[46] Caihong Mu, Haikun Yu, Keyang Zhang, Qiang Tian, Yi Liu*. AutoMaster: Differentiable Graph Neural Network Architecture Search for Collaborative Filtering Recommendation[C]. 24th International Conference on Web Engineering (ICWE), Tampere, Finland, June 17-20, 2024. (CCF推荐C类会议, 录取率当年为24%左右)

[45] Aamir Ali, Caihong Mu, Zeyu Zhang, Jian Zhu, Yi Liu*. A two-branch multiscale spectral-spatial feature extraction network for hyperspectral image classification[J]. Journal of Information and Intelligence, 2024, 2(3): 224–235.

[44] 黄河源, 慕彩红*, 方云飞, 刘逸. 使用图负采样的图卷积神经网络推荐算法[J]. 西安电子科技大学学报, 2024, 51(1): 86-99.

[43] Caihong Mu, Heyuan Huang, Yunfei Fang, Yi Liu*. A Graph Convolutional Neural Network for Recommendation Based on Community Detection and Combination of Multiple Heterogeneous Graphs[C]. 23nd IEEE International Conference on Data Mining (ICDM), Shanghai, China, Dec. 1-4, 2023. (CCF推荐B类会议, 录取率当年为20%左右)

[42] Yunfei Fang, Caihong Mu, Yi Liu*. AutoShape: Automatic Design of Click-Through Rate Prediction Models Using Shapley Value[C]. 20th Pacific Rim International Conference on Artificial Intelligence (PRICAI), Jakarta, Indonesia, Nov. 15-19, 2023. (录取为长文Regular Paper, CCF推荐C类会议, 长文录取率当年为25%左右)

[41] Jian Zhu, Yi Liu*, Jiajie Feng, Caihong Mu. A Multi-scale Densely Connected and Feature Aggregation Network for Hyperspectral Image Classification[C]. 20th Pacific Rim International Conference on Artificial Intelligence (PRICAI), Jakarta, Indonesia, Nov. 15-19, 2023. (录取为长文Regular Paper, CCF推荐C类会议, 长文录取率当年为25%左右)

[40] Caihong Mu, Zeyu Zhang*, Suling Chen, Yi Liu. A Dual-Branch Network Based on Transformer and Depthwise Convolution for Hyperspectral Image Classification[C]. 2023 International Conference on Cyber-Physical Social Intelligence (ICCSI), Xi'an, China, Oct. 20-23, 2023.

[39] Yi Liu, Jian Zhu, Jiajie Feng, Caihong Mu*. A Feature Embedding Network with Multiscale Attention for Hyperspectral Image Classification[J]. Remote Sensing, 2023, 15(13): 3338.

[38] Caihong Mu, Xin Tang, Jiashen Luo*, Yi Liu. GMiRec: A Multi-image Visual Recommendation Model Based on a Gated Neural Network[C]. 16th International Conference on Knowledge Science, Engineering and Management (KSEM), Guangzhou, China, Aug. 16-18, 2023. (录取为长文Full Paper, CCF推荐C类会议, 长文录取率常年为20%左右)

[37] Caihong Mu, Jiahui Ying, Yunfei Fang*, Yi Liu. A Graph Neural Network for Cross-domain Recommendation Based on Transfer and Inter-domain Contrastive Learning[C]. 16th International Conference on Knowledge Science, Engineering and Management (KSEM), Guangzhou, China, Aug. 16-18, 2023. (CCF推荐C类会议, 录取率常年为30%左右)

[36] Jiahuan Chen*, Caihong Mu, Mohammed Alloaa, Yi Liu. A Hypergraph Augmented and Information Supplementary Network for Session-Based Recommendation[C]. 16th International Conference on Knowledge Science, Engineering and Management (KSEM), Guangzhou, China, Aug. 16-18, 2023. (CCF推荐C类会议, 录取率常年为30%左右)

[35] Mu Caihong, Huang Heyuan*, Liu Yi, Luo Jiashen. Graph Convolutional Neural Network based on the Combination of Multiple Heterogeneous Graphs[C]. 22nd IEEE International Conference on Data Mining Workshops (ICDMW), Orlando, FL, USA, Nov. 28 - Dec. 1, 2022.

[34] Mu Caihong, Dong Zhidong, Liu Yi*. A Two-Branch Convolutional Neural Network Based on Multi-Spectral Entropy Rate Superpixel Segmentation for Hyperspectral Image Classification[J]. Remote Sensing, 2022; 14(7):1569.

[33] Mu Caihong*, Chen Weizhu, Liu Yi, Lei Dongchang, Liu Ruochen. Virtual Information Core Optimization for Collaborative Filtering Recommendation Based on Clustering and Evolutionary Algorithm[J]. Applied Soft Computing, 2022, 116: 108355.

[32] Mu Caihong*, Zeng Qize, Liu Yi, Qu Yi. A Two-Branch Network Combined With Robust Principal Component Analysis for Hyperspectral Image Classification[J]. IEEE Geoscience and Remote Sensing Letters, 2021, 18(12): 2147-2151.

[31] Mu Caihong, Liu Yijin, Liu Yi*. Hyperspectral Image Spectral–Spatial Classification Method Based on Deep Adaptive Feature Fusion[J]. Remote Sensing, 2021, 13(4): 746.

[30] Liu Jing*, Yang Zhe, Liu Yi, Mu Caihong. Hyperspectral Remote Sensing Images Deep Feature Extraction Based on Mixed Feature and Convolutional Neural Networks[J]. Remote Sensing, 2021, 13(13): 2599.

[29] Liu Jing*, Zhang You, Liu Yi, Mu Caihong. Hyperspectral Images Unmixing Based on Abundance Constrained Multi-Layer KNMF[J]. IEEE Access, 2021, 9: 91080-91090.

[28] Guo Zhen, Mu Caihong*, Liu Yi. A Multi-Branch Network based on Weight Sharing and Attention Mechanism for Hyperspectral Image Classification[C]. IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2021: 5370-5373.

[27] Mu Caihong*, Guo Zhen, Liu Yi*. A Multi-Scale and Multi-Level Spectral-Spatial Feature Fusion Network for Hyperspectral Image Classification[J]. Remote Sensing, 2020, 12(1): 125, 1-23.

[26] Mu Caihong*, Liu Jian, Liu Yi, Liu Yijin. Hyperspectral Image Classification Based on Active Learning and Spectral-Spatial Feature Fusion using Spatial Coordinates[J]. IEEE Access, 2020, 8: 6768-6781.

[25] Liu Jing*, Guo Ximei, Liu Yi. Hyperspectral remote sensing image feature extraction based on spectral clustering and subclass discriminant analysis[J]. Remote Sensing Letters, 2020, 11(2): 166-175.

[24] Mu Caihong*, Li Chengzhou, Liu Yi, Qu Rong, Jiao Licheng. Accelerated genetic algorithm based on search-space decomposition for change detection in remote sensing images[J]. Applied Soft Computing, 2019, 84: 105727, 1-16.

[23] Mu Caihong, Zhang Jian, Liu Yi*, Qu Rong, Huang Tianhuan. Multi-objective ant colony optimization algorithm based on decomposition for community detection in complex networks[J]. Soft Computing, 2019, 23: 12683-12709.

[22] Liu Jing*, Li Qingyan, Liu Yi. Spectral feature extraction of hyperspectral remote sensing images based on class pair-weighted criterion[J]. Journal of Applied Remote Sensing, 2019, 13(4): 046504.

[21] 慕彩红, 吴生财, 刘逸*, 彭鹏, 刘若辰. SAR图像NSCT域显著图去噪变化检测[J]. 西安电子科技大学学报, 2018, 45(2): 19-25.

[20] 慕彩红, 柴文壹, 刘逸*, 刘敬. 一种改进的网络鲁棒性与有效性增强方法[J]. 西安电子科技大学学报, 2018, 45(4): 6-11.

[19] Liu Ruochen*, Li Jianxia, Fan Jing, Mu Caihong, Jiao Licheng. A coevolutionary technique based on multi-swarm particle swarm optimization for dynamic multi-objective optimization[J]. European Journal of Operational Research, 2017, 261(3): 1028-1051.

[18] Mu Caihong*, Cheng Huiwen, Feng Wei, Liu Yi, Qu Rong. Information Core Optimization Using Evolutionary Algorithm with Elite Population in Recommender Systems[C]. IEEE Congress on Evolutionary Computation (CEC), 2017: 1143-1149.

[17] Mu Caihong*, Li Chengzhou, Liu Yi, Sun Menghua, Jiao Licheng and Qu Rong. Change Detection in SAR Images Based on the Salient Map Guidance and an Accelerated Genetic Algorithm[C]. IEEE Congress on IEEE Evolutionary Computation (CEC), 2017: 1150-1157.

[16] Mu Caihong*, Xie Jin, Liu Yong, Chen Feng, Liu Yi, Jiao Licheng. Memetic Algorithm with Simulated Annealing Strategy and Tightness Greedy Optimization for Community Detection in Networks[J]. Applied Soft Computing, 2015, 34: 485-501.

[15] Liu Yi*, Mu Caihong, Kou Weidong, Liu Jing. Modified particle swarm optimization-based multilevel thresholding for image segmentation[J]. Soft Computing, 2015, 19(5): 1311-1327.

[14] Mu Caihong*, Jiao Licheng, Liu Yi, Li Yangyang. Multiobjective nondominated neighbor coevolutionary algorithm with elite population[J]. Soft Computing, 2015, 19(5): 1329-1349.

[13] 慕彩红*, 霍利利, 刘逸, 刘若辰，焦李成. 基于小波融合和PCA-核模糊聚类的遥感图像变化检测[J]. 电子学报, 2015, 43(7): 1375-1381.

[12] 刘逸*, 慕彩红, 刘敬. 结合邻域信息粒子群聚类用于SAR图像变化检测[J]. 西安电子科技大学学报, 2015, 42(1): 187-193.

[11] Liu Ruochen*, Niu Xu, Fan Jing, Mu Caihong, Jiao Licheng. An orthogonal predictive model-based dynamic multi-objective optimization algorithm[J]. Soft Computing, 2015, 19(11): 3083-3107.

[10] Mu Caihong*, Liu Yong, Liu Yi, Wu Jianshe, Jiao Licheng. Two-stage algorithm using influence coefficient for detecting the hierarchical, non-overlapping and overlapping community structure[J]. Physica A: Statistical Mechanics and its Applications, 2014, 408: 47-61.

[9] Liu Ruochen*, Chen Yangyang, Ma Wenping, Mu Caihong, Jiao Licheng. A novel cooperative coevolutionary dynamic multi-objective optimization algorithm using a new predictive model[J]. Soft Computing, 2014, 18(10): 1913-1929.

[8] Liu Ruochen*, Wang Lixia, Ma Wenping, Mu Caihong, Jiao Licheng. Quadratic interpolation based orthogonal learning particle swarm optimization algorithm[J]. Natural Computing, 2014, 13(1): 17-37.

[7] Mu Caihong*, Xie Jin, Liu Ruochen, Jiao Licheng. A memetic algorithm using local structural information for detecting community structure in complex networks[C]. IEEE Congress on Evolutionary Computation (CEC), 2014: 680-686.

[6] Mu Caihong*, Zhang Jian, Jiao Licheng. An intelligent ant colony optimization for community detection in complex networks[C]. IEEE Congress on Evolutionary Computation (CEC), 2014: 700-706.

[5] 刘逸*, 寇卫东, 慕彩红. 结合多阈值法的模糊聚类用于SAR图像变化检测[J]. 西安电子科技大学学报, 2013, 40(6): 13-18.

[4] 慕彩红*, 焦李成, 刘逸. M-精英协同进化算法求解约束优化问题[J]. 西安电子科技大学学报, 2010, 37(5): 2443-2448.

[3] 慕彩红*, 焦李成, 刘逸. M-精英协同进化数值优化算法[J]. 软件学报, 2009, 20(11): 2925-2938.

[2] 慕彩红*, 焦李成, 刘逸. M-精英进化算法及其在V-BLAST系统中的应用[J]. 电子与信息学报, 2009, 31(10): 2443-2448.

[1] Mu Caihong*, Zhu Mingming. Clonal selection detection algorithm for the V-BLAST system[C]. International Conference on Natural Computation (ICNC), 2006: 402-411.

研究生毕业去向：

2025年，毕业6人（其中三人在校期间获得国奖奖学金，两人被评为校优秀硕士学位获得者），毕业去向：北京三快在线科技有限公司（美团）；上海华为技术有限公司（2人）；北京百度在想网络技术有限公司；西北工业大学（读博）；西安电子科技大学（读博）

2024年，毕业5人，毕业去向：北京三快在线科技有限公司（美团，上海）；中国农业银行西安研发中心；宁德新能源科技有限公司；中国农业发展银行（合肥）；交通银行（上海）

2023年，毕业3人，毕业去向：北京三快在线科技有限公司（美团）；华为技术有限公司（华为）；深圳欢太科技有限公司（OPPO）

2022年，毕业3人，毕业去向：北京三快在线科技有限公司（美团）；百度在线网络技术（北京）有限公司（百度）；阿里巴巴科技（北京）有限公司（阿里）

2021年，毕业4人，毕业去向：北京字节跳动科技有限公司；华为技术有限公司；北京京东世纪贸易有限公司2人。

2020年，毕业4人，毕业去向：浙江大华技术股份有限公司；上海集成电路研发中心；中国移动通信有限公司研究院；中国农业银行研发中心（西安）。

2019年，毕业3人，毕业去向：上海众源网络有限公司（上海爱奇艺）；北京陌陌信息科技有限公司；招银网络科技有限公司。

2018年，毕业4人，毕业去向：北京三快在线科技有限公司（美团点评北京）；中国船舶重工集团公司第七一六研究所；Vivo移动通信通信有限公司（深圳）；西安深迈瑞医疗电子研究院有限公司。

2017年，毕业4人，毕业去向：西安华为技术有限公司；创维集团有限公司；联咏电子科技（西安）有限公司；中国人民解放军新疆军区（强军）。

2016年，毕业4人，毕业去向：中电集团20所；展讯通信（上海）；南京海兴电网技术有限公司；平安科技（深圳）有限公司。

2015年，毕业5人，毕业去向：深圳华为；西安中兴移动；北方信息控制集团有限公司(南京)；上海展讯；西安航天天绘。

2014年，毕业2人，毕业去向：青岛鼎信通讯股份有限公司；国家密码管理局商用密码检测中心。