个人简介：

张若楠，博士，准聘副教授，硕士生导师，毕业于北京大学。研究方向：量子启发式多源异构信息感知、推理与决策、面向人机感知共友好的多媒体处理与分析（感知、融合、检索增强等）、情感计算。曾就职于华为技术有限公司与鹏城实验室。近年来在智能交通、遥感等领域顶级期刊发表SCI TOP期刊及国际会议24余篇，主持国家级项目1项，银川市项目1项，参与省部级以上项目4项、已授权专利5项。目前为多个相关领域期刊、会议审稿人。邮箱：zhangrn@nxu.edu.cn。个人主页：https://zhangrn123-github-io.pages.dev/

招生信息：

1.专业范围：计算机类、数学类、电子信息类、自动化类等信息科学类专业的本科和硕士毕业生。

2.研究/开发能力：熟练的程序设计能力，具有一定的探索能力和创新精神。

3.其他要求：对做科研工作有热情、有兴趣，自我驱动力强。

科研情况：

1.主持国家自然科学基金青年基金（青C）项目“量子启发式点云场景识别方法研究”（No.62506179，2026.01-2028.12，30万元）;

2.主持银川市基础研究项目“非结构场景异构信息的主动感知技术研究”（No.YCHT2025241，2025.7-2027.6, 8万元）；

3.主持2026年国际足联世界杯博士科研启动费项目1项（2024, 20万元）；

4.参与完成科技创新2030-“新一代人工智能”重大项目子课题1项(2020.9-2023.6, 5325万元)

5.参与完成广东省重点领域研究计划1项(2019.9-2021.8)，

6.参与在研国家自然科学基金面上项目1项（2022.01-2025.12, 60万元），

科研成果：

以第一/通讯作者发表SCI TOP期刊5篇T1 1篇，共计发表24篇SCITOP期刊以及CCF推荐高质量国际会议，获得深圳市优秀论文奖，论文引用556次以上，H-Index=6。

【代表性期刊论文】

[1]Ruonan Zhang, Ge Li*, Wei Gao, andShan Liu.A Quantum-Inspired Framework in Leader-Servant Mode for Large-Scale Multi-Modal Place Recognition, IEEE Transactions on Intelligent Transportation Systems(TITS), vol. 26, no. 2, pp. 2027-2039, Feb. 2025,doi: 10.1109/TITS.2024.3497574. (SCI TOP,IF:8.4)

[2]Ruonan Zhang, Ge Li*, Wei Gao, and Thomas H. Li. ComPoint: Can Complex-valued Point Cloud Feature Representation Benefit for Place Recognition? IEEE Transactions on Intelligent Transportation Systems (TITS), pp. 1-14,2024,doi: 10.1109/TITS.2024.3351215. (SCI TOP, IF:8.4)

[3]Ruonan Zhang, Jingyi Chen, Wei Gao*, Ge Li and Thomas H. Li. PointOT: Interpretable Geometry-Inspired Point Cloud Generative Model via Optimal Transport. IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), vol. 32, no. 10, pp. 6792-6806, 2022, doi: 10.1109/TCSVT.2022.3170588. (SCI TOP, IF:11.1)

[4]Ruonan Zhang, Wei Gao*, Ge Li, and Thomas H. Li. QINet: Decision Surface Learning and Adversarial Enhancement for Quasi-Immune Completion of Diverse Corrupted Point Clouds. IEEE Transactions on Geoscience and Remote Sensing (TGRS),vol. 60, pp. 1-14, 2022, doi: 10.1109/TGRS.2022.3220198. (SCI TOP, IF: 8.6)

[5]RuonanZhangand Wenmin. Wang, "Second- and High-Order Graph Matching for Correspondence Problems," inIEEE Transactions on Circuits and Systems for Video Technology, vol. 28, no. 10, pp. 2978-2992, Oct. 2018, doi: 10.1109/TCSVT.2017.2718225.(SCI TOP,IF:11.1)

[6]JiapengLi,RruonanZhang, GeLi and ThomasLi.SDE2D: Semantic-Guided Discriminability Enhancement Feature Detector and Descriptor,IEEE Transactions on Multimedia(TMM), vol. 27, pp. 275-286, 2025, doi: 10.1109/TMM.2024.3521748.(SCI TOP, IF:9.6)

【代表性会议论文】

[1]Wei Yan,Ruonan Zhang*, Jing Wang, Shan Liu, Thomas H. Li, and Ge Li. 2020. Vaccine-style-net: Point Cloud Completion in Implicit Continuous Function Space. In Proceedings of the 28th ACM International Conference on Multimedia (MM '20). Association for Computing Machinery, New York, NY, USA, 2067–2075. (EI/ISTP检索，CCF A)

[2]Ruonan Zhang, Xiaohang Liu, Ge Li*, Thomax H. Li, and Pengjun Zhao. Sketch-aided with Interactive Fusion Point Cloud Place Recognition. Proceedings oftheACM SIGMM International Conference on Multimedia Retrieval (ICMR),Phuket, Thailand, June 10-14,2024.(EI/ISTP检索，CCF B)

[3]Ge Li andRuonan Zhang*. A Point is a Wave: Point-Wave Network for Place Recognition.Proceedings of theInternational Conference on Acoustics, Speech, and Signal Processing (ICASSP), Rhodes Island, Greece, June 4-10,2023.(EI/ISTP检索，CCF B)

[4]Ruonan Zhang, Wenmin Wang and Ronggang Wang.A K-Nearest-Neighbor-Pooling method for graph matching,IEEE International Conference on Multimedia & Expo Workshops (ICMEW), Seattle, WA, 2016, pp. 1-6. (EI/ISTP检索，CCF B)

[5]RuonanZhang,YuruiRen,Jingfei Qiu, et al. Base-detail image inpainting.[C]//BMVC. 2019: 195. (EI/ISTP检索，CCF C)

[6]Ruonan Zhangand Wenmin Wang.An MCMC-based prior sub-hypergraph matching in presence of outliers,23rd International Conference on Pattern Recognition (ICPR), Cancun, 2016, pp. 799-804. (EI/ISTP检索，CCF C)

[7]RuonanZhangandWenminWang.An advanced local offset matching strategy for object proposal matching,IEEEVisual Communications and Image Processing (VCIP), Chengdu, China, 2016, pp. 1-4. (EI/ISTP检索)

【授权专利】

[1]一种量子态点云的特征提取方法、装置及电子设备，专利号：ZL202310732308.4

[2]一种基于几何可解释的点云生成方法，专利号：ZL202110731635.9

[3]基于图的渐进式点云下采样方法及装置，专利号：ZL202010816477.2

[4]基于显著性特征的模拟残缺点云的遮罩生成方法，专利号：ZL202010620484.5

[5]一种基于空间频率的提升自监督弹幕深度估计模型性能的方法及装置，专利号：ZL202210392984.7

【著作】

1、《Deep Learning for 3D Point Clouds》，参编