严双林，南京林业大学信息科学技术学院/人工智能学院校聘副教授。2025年1月于南京理工大学获得博士学位，随后加入香港理工大学从事博士后研究工作，2026年1月以F类副教授人才引进方式入职南京林业大学，并加入由国家杰青唐金辉教授领导的多模态智能体实验室（Multimodal Intelligent Agent Group，MIAG）。研究方向为计算机视觉、多媒体分析与理解，主要聚焦于以人为中心的视觉理解以及多模态视觉理解研究。在人工智能与计算机视觉领域发表学术论文 20 余篇，包括国际顶级会议AAAI、ACM MM、IJCAI和期刊IEEE TIP、IEEE TIFS、IEEE TNNLS、IEEE TCSVT、Information Fusion等，谷歌学术引用 1000 余次。

真诚地欢迎对人工智能、计算机视觉领域感兴趣的同学报考课题组的硕士、博士研究生！欢迎有较好的数学、英语基础和较强编程能力的同学通过邮件（shuanglinyan@njfu.edu.cn）与我联系。将尽最大的努力培养好学生，提供全方位科研指导，培养独立思考能力，孵化高质量成果，塑造优良综合素质。优秀者可推荐至国内外顶尖团队深造/交流。

课题组全年招收本科实习生（不限专业），欢迎对人工智能相关应用有浓厚兴趣的同学加入，表现优秀者可优先推荐留组或推荐至国内外顶尖团队深造。

[1] Shuanglin Yan, Neng Dong, Liyan Zhang, Jinhui Tang. CLIP-Driven Fine-grained Text-Image Person Re-identification. IEEE Transactions on Image Processing (IEEE TIP), 2023. [CCF-A] [中科院一区Top] [JCR Q1] [ESI Highly Cited Paper]

[2] Shuanglin Yan, Hao Tang, Liyan Zhang, Jinhui Tang. Image-Specific Information Suppression and Implicit Local Alignment for Text-based Person Search. IEEE Transactions on Neural Networks and Learning Systems (IEEE TNNLS), 2024. [中科院一区Top] [JCR Q1]

[3] Shuanglin Yan, Neng Dong, Jun Liu, Liyan Zhang, Jinhui Tang. Learning Comprehensive Representations with Richer Self for Text-to-Image Person Re-Identification. ACM International Conference on Multimedia (ACM MM), 2023. [CCF-A]

[4] Shuanglin Yan, Jun Liu, Neng Dong, Liyan Zhang, Jinhui Tang. Prototypical Prompting for Text-to-Image Person Re-Identification. ACM International Conference on Multimedia (ACM MM), 2024. [CCF-A]

[5] Shuanglin Yan, Jun Liu, Neng Dong, Liyan Zhang, Jinhui Tang. Cross-modal Collaborative Representation Learning for Text-to-Image Person Retrieval. International Joint Conference on Artificial Intelligence (IJCAI), 2025. [CCF-A, Oral]

[6] Hao Tang, Yu Liu, Shuanglin Yan^* (通讯作者), Fei Shen, Shengfeng He, Jing Qin. Cross-modal Proxy Evolving for OOD Detection with Vision-Language Models, AAAI Conference on Artificial Intelligence (AAAI), 2026. [CCF-A]

[7] Shuanglin Yan, Yafei Zhang, Minghong Xie, Dacheng Zhang, Zhengtao Yu. Cross-domain Person Re-Identification with Pose-Invariant Feature Decomposition and Hypergraph Structure Alignment. Neurocomputing, 2022. [中科院二区] [JCR Q1]

[8] Shuanglin Yan, Neng Dong, Shuang Li, Huafeng Li. TriMatch: Triple Matching for Text-to-Image Person Re-Identification. IEEE Signal Processing Letters (IEEE SPL), 2025. [中科院三区] [JCR Q2]

[9] Huafeng Li, Shuanglin Yan, Zhengtao Yu, Dapeng Tao.Attribute-Identity Embedding and Self-supervised Learning for Scalable Person Re-Identification. IEEE Transactions on Circuits and Systems for Video Technology (IEEE TCSVT), 2020. [中科院一区Top] [JCR Q1]

[10] Neng Dong, Shuanglin Yan, Liyan Zhang, Jinhui Tang. Multi-View Information Integration and Reasoning Network for Occluded Person Re-Identification. Information Fusion (INFUS), 2024. [中科院一区Top] [JCR Q1]

[11] Neng Dong, Shuanglin Yan, Liyan Zhang, Jinhui Tang. Richer Semantics, Better Alignment: Aligning Visual Features with Explicit and Enriched Semantics for Visible-Infrared Person Re-Identification. International Joint Conference on Artificial Intelligence (IJCAI), 2025. [CCF-A]

[12] Neng Dong, Shuanglin Yan, Liyan Zhang, Jinhui Tang. Diverse Semantics-Guided Feature Alignment and Decoupling for Visible-Infrared Person Re-Identification. IEEE Transactions on Information Forensics and Security (IEEE TIFS), 2025. [CCF-A] [中科院一区Top] [JCR Q1]

[13] Neng Dong, Liyan Zhang, Shuanglin Yan, Hao Tang, Jinhui Tang. Erasing, Transforming, and Noising Defense Network for Occluded Person Re-Identification. IEEE Transactions on Circuits and Systems for Video Technology (IEEE TCSVT), 2024. [中科院一区Top] [JCR Q1]

[14] Hao Tang, Jun Liu, Shuanglin Yan, Rui Yan, Zechao Li, Jinhui Tang. M3Net: Multi-view Encoding, Matching, and Fusion for Few-shot Fine-grained Action Recognition. ACM International Conference on Multimedia (ACM MM), 2023. [CCF-A]

(1) 国家自然科学基金重点项目“面向大数据环境的高通量视觉计算”（批准号：61732007），2018年1月至2022年12月，参与

(2) 科技创新2030“新一代人工智能”重大项目课题“分布式跨媒体知识获取与管理”（课题号: 2018AAA0102002），2019年12月至2023年12月，参与

(3) 国家自然科学基金地区项目“基于对抗自编码的姿态鲁棒与域不变无监督行人再识别研究”（批准号：61966021）， 2020年1月至2023年12月，参与