白静，西安电子科技大学人工智能学院教授，博士生导师，西安市“类脑计算与深度学习”重点实验室副主任，智能视频追踪与识别实验室负责人。“智能感知与图像理解教育部重点实验室”骨干成员，“西电-维恩 AI Plus研究中心”副主任，“国际智能感知与计算国际联合研究中心”骨干成员，教育部“长江学者和创新团体发展计划”创新团队主要成员，国家“111计划”创新引智基地骨干成员，“智能感知与计算教学示范中心”骨干成员。 现为IEEE高级会员，中国计算机学会高级会员。

负责并主持国家自然科学基金面上项目1项、中国电科集团技术研发项目4项，国防重点实验室课题1项，国家自然科学基金青年项目1项、高等学校博士学科点专项科研基金1项、中国博士后科学基金面上项目1项，中国博士后特别资助项目1项，中央高校基本科研业务费专项资金项目3项，中兴通讯产学研项目1项，航天科工集团预研项目1项，华为辅助驾驶研发项目1项，中国博士后首批国际交流计划派出项目1项，中科院光谱成像技术国家重点实验室课题1项，积累到款500余万。参与自然基金重大研究计划、国家“863计划”，部委预研以及企业产学研项目若干。近年来共发表学术论文40余篇，多次入选ESI全球TOP 1%高被引论文，授权发明专利20余项，软件著作权1项，合作出版学术专著2部。近年来实现成果转化3项，主持多个校企政联合项目，负责搭建“平安校园智能视频分析预警系统”和西安市“碑林小二-城市智能管理平台”。

一流课程《图像理解与计算机视觉》主讲人。

相关信息欢迎访问校内主页：https://web.xidian.edu.cn/baijing/index.html

DBLP学术主页：https://dblp.org/pid/35/328-3.html

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研究方向

十余年来带领研究团队面向国家重大战略需求，追踪国际前沿发展，借鉴国际人工智能研究领域的科研模式，有效整合创新资源，解决复杂影像数据动态、异构和高维等特征显著增加带来的知识表达困难等问题，重点突破计算智能与机器学习理论研究、大数据深度学习、视频智能分析与目标识别、高分辨影像感知与解译等方面的科学问题。

目前主要的研究方向包括：

• 无线电与电磁信号感知

• 大数据深度学习与应用

• 高分辨遥感影像解译与分析

• 视频智能分析与目标识别

• 危害行为识别与预警等技术

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招生要求

接收硕士/博士研究生报考，接收工程博士报考，欢迎加入我们团队。

招生要求：接收人工智能、计算机、电信等相关专业；英语达到四六级水平；具有较好的数学、编程和专业课基础；有项目和竞赛经验者优先，立志读博者优先。

报考之前请邮件与老师取得联系。

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研究工作经历

• 2021/08 - 至今，西安电子科技大学，人工智能学院教授、博士生导师

• 2017/11 - 2021/07，西安电子科技大学，人工智能学院副教授/博士生导师

• 2011/07 - 2017/11，西安电子科技大学，电子工程学院，教师/副教授

• 2014/07 - 2015/12，美国威斯康辛大学麦迪逊分校，空间科学与工程中心，访问学者&Honorary Fellow

• 2009/12 - 2011/06，西安电子科技大学，电子工程学院，教师/讲师

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近年成果

[1].Jing Bai, Wei Shi, Zhu Xiao, et al., Achieving Better Category Separability for Hyperspectral Image Classification: A Spatial–Spectral Approach. IEEE Transactions on Neural Networks and Learning Systems, Jan. 2023, DOI: 10.1109/TNNLS.2023.3235711 (中科院一区, IF: 10.4)NEW！

[2].Jing Bai, Junjie Ren, Zhu Xiao, et al., Localizing From Classification: Self-Directed Weakly Supervised Object Localization for Remote Sensing Images. IEEE Transactions on Neural Networks and Learning Systems, Sep. 2023, DOI: 10.1109/TNNLS.2023.3309889 (中科院一区, IF: 10.4)NEW！

[3].Jing Bai, Ruotong Liu, Haisheng Zhao, et al., Hyperspectral Image Classification Using Geometric Spatial-Spectral Feature Integration: A Class Incremental Learning Approach. IEEE Transactions on Geoscience and Remote Sensing, Nov. 2023, DOI: 10.1109/TGRS.2023.3333005. (中科院一区, IF: 8.2)NEW！

[4].Xuebo Liu, Yiran Wang,Jing Bai*, Haoran Li, Xu Wang, An Imbalanced Signal Modulation Classification and Evaluation Method Based On Synthetic Minority Over-Sampling Technique. IEEE IGARSS, Oct. 2023, Pasadena, CA, USA.NEW！

[5].Jing Bai, Anran Yuan, Zhu Xiao, Huaji Zhou, Dingchen Wang, Hongbo Jiang, LichengJiao. Class Incremental Learning with Few-Shots Based on Linear Programming for Hyperspectral Image Classification. IEEE Transactions on Cybernetics, vol. 52, no.6, 2022, pp. 5474- 5485. (中科院SCI一区, IF: 19.118)入选全球ESI TOP 1%高被引论文

[6].Jing Bai, Yiran Wang, Zhu Xiao, et al., RffAe-S: Autoencoder Based on Random Fourier Feature with Separable Loss for Unsupervised Signal Modulation Clusterin, IEEE Transactions on Industrial Informatics, online, May. 2022, DOI: 10.1109/TII.2022.3171349. (中科院一区, IF: 11.648)

[7].Yiran Wang,Jing Bai*, Zhu Xiao, Huaji Zhou, Licheng Jiao. MsmcNet: A Modular Few-shot Learning Framework for Signal Modulation Classification, IEEE Transactions on Siganl Processing, DOI:10.1109/TSP.2022.3191783. (中科院一区, IF: 4.875)

[8].Jing Bai, Zheng Wen, Zhu Xiao, et al., Hyperspectral Image Classification Based on Multibranch Attention Transformer Networks, IEEE Transactions on Geoscience and Remote Sensing, online, Aug. 2022, DOI: 10.1109/TGRS.2022.3196661 (中科院二区, IF: 8.125)

[9].Jing Bai, Shaojie Huang, Zhu Xiao, et al., Few-Shot Hyperspectral Image Classification Based on Adaptive Subspaces and Feature Transformation, IEEE Transactions on Geoscience and Remote Sensing, online, Feb. 2022, DOI: 10.1109/TGRS.2022.3149947. (中科院二区, IF: 8.125)

[10].Jing Bai, Wei Shi, Zhu Xiao, Amelia C Regan, Talal Ahmed Ali Ali, Yongdong Zhu, Rui Zhang, Licheng Jiao. Hyperspectral Image Classification based on Superpixel Feature Subdivision and Adaptive Graph Structure. IEEE Transactions on Geoscience and Remote Sensing, online, Feb. 2022. DOI: 10.1109/TGRS.2022.3153446. (中科院二区, IF: 8.125)

[11].Huaji Zhou,Jing Bai*, Linchun Niu, Jie Xu, Zhu Xiao, Shilian Zheng, Licheng Jiao and Xiaoniu Yang. Electromagnetic Signal Classification Based on Class Exemplar Selection and Multi-Objective Linear Programming. Remote Sensing, Jan. 2022, 14(5), 1177, DOI: 10.3390/rs14051177. (中科院二区, IF: 5.349)

[12].Jing Bai, Jiawei Lu, Zhu Xiao, Zheng Chen, Licheng Jiao. Generative Adversarial Networks Based on Transformer Encoder and Convolution Block for Hyperspectral Image Classification, Remote Sensing, 2022, DOI: 10.3390/rs14143426. (中科院二区, IF: 5.349)

[13].Huaji Zhou,Jing Bai*, Yiran Wang, Junjie Ren, Xiaoniu Yang, Licheng Jiao. Deep Radio Signal Clustering with Interpretability Analysis Based on Saliency Map, Digital Communications and Networks, 2022, accepted. (中科院一区, IF: 6.348)

[14]Huaji Zhou, Xu Wang,Jing Bai*, Zhu Xiao. Modulation signal recognition based on selective knowledge transfer. IEEE Global Communications Conference, 2022.

[15].Huaji Zhou, Zichen Zhou,Jing Bai*. Electromagnetic Signal Modulation Classification based on Multimodal Features and Reinforcement Learning, IEEE World Congress on Computational Intelligence WCCI 2022.

[16].Jing Bai, Wentao Yu, Zhu Xiao. Two-Stream Spatial-Temporal Graph Convolutional Networks for Driver Drowsiness Detection. IEEE Transactions on Cybernetics, online, Oct. 2021, DOI: 10.1109/TCYB.2021.3110813. (中科院SCI一区, IF: 19.118)

[17].Jing Bai, Bixiu Ding, Zhu Xiao, Licheng Jiao, Hongyang Chen, and Amelia C. Regan. Hyperspectral Image Classification Based on Deep Attention Graph Convolutional Network. IEEE Transactions on Geoscience and Remote Sensing, online, Mar. 2021, DOI: 10.1109/TGRS.2021.3066485. (中科院二区, IF: 8.125)入选全球ESI TOP 1%高被引论文

[18].Jing Bai, Junjie Ren, Yujia Yang, Zhu Xiao, Wentao Yu, Vincent Havyarimana, and Licheng Jiao. Object Detection in Large-Scale Remote-Sensing Images Based on Time- Frequency Analysis and Feature Optimization. IEEE Transactions on Geoscience and Remote Sensing, online, Oct. 2021，DOI: 10.1109/TGRS.2021.3119344. (中科院二区, IF: 8.125)

[19].Huaji Zhou,Jing Bai*, Yiran Wang, Licheng Jiao, Shilian Zheng, Weiguo Sheng, Jie Xu, Xiaoniu Yang, Few-shot electromagnetic signal classification: A data union augmentation method. Chinese Journal of Aeronautics, online, Sep. 2021. DOI: 10.1016/j.cja.2021.07.014. (中科院SCI一区, IF: 4.061)

[20].Jing Bai, Wentao Yu, Anran Yuan and Zhu Xiao, Airplane Detection in Optical Remote Sensing Video Using Spatial and Temporal Features, 2020 International Joint Conference on Neural Networks (IJCNN), Glasgow, UK, 2020. July, 20006630.

[21].Zhu Xiao, Fancheng Li; Hongbo Jiang,Jing Bai, Jisheng Xu, Fanzi Zeng, Min Liu. A Joint Information and Energy Cooperation Framework for CR-Enabled Macro-Femto Heterogeneous Networks, IEEE Internet of Things Journal, vol. 7, no. 4, pp. 2828-2839, April 2020, DOI: 10.1109/JIOT.2019.2962863.

[22].Vincent Havyarimana, Zhu Xiao, Alexis Sibomana, Di Wu, andJing Bai. "A Fusion Framework based on Sparse Gaussian-Wigner Prediction for Vehicle Localization using GDOP of GPS Satellites". IEEE Transactions on Intelligent Transportation Systems, Feb., 2020, Vol. 21, No. 2, pp: 680-689.

[23].Jianhua Xiao, Zhu Xiao, Dong Wang,Jing Bai, Vincent Havyarimana, Fanzi Zeng. Short-term traffic volume prediction by ensemble learning in concept drifting environments. Knowledge-Based Systems, vol. 164, no. 15, Jan. 2019, pp. 213-225. DOI: 10.1016/j.knosys.2018.10.037.

[24].Yourong Huang, Zhu Xiao, Xiaoyou Yu, Dong Wang, Vincent Havyarimana,Jing Bai. "Road Network Construction with Complex Intersections based on Sparsely-Sampled Private Car Trajectory Data". ACM Transactions on Knowledge Discovery from Data (TKDD), Vol. 13, No. 3, Article 35. June 2019, 28 pages. https://doi.org/10.1145/3326060

[25].Jie Chen; Zhu Xiao*; Dong Wang; Daiwu Chen; Vincent Havyarimana;Jing Bai; Hongyang Chen. "Towards Opportunistic Compression and Transmission for Private Car Trajectory Data Collection". IEEE Sensors Journal, March 1, 2019, 19(5): 1925-1935.

[26].Jing Bai, Shu Song. "Medical Image Denoising Based on Sparse Dictionary Learning and Cluster Ensemble", Soft Computing. 2018, 22(5): 1467-1473.

[27].Wei Zhao, Liangjie Xu,Jing Bai*, Jiateng Yin, Bin Ran, "Sensor-Based Risk Perception Ability Network Design for drivers in Snow and Ice Environmental Freeway: A Deep Learning and Rough Sets Approach". Soft Computing, 2018, 22(5): 1457–1466. (SCI, IF: 2.47).

[28].Jing Bai, Wenhao Zhang, Zhenzhen Gou, Licheng Jiao, Nonlocal-Similarity-Based Sparse Coding for Hyperspectral Imagery Classification. IEEE Geoscience and Remote Sensing Letters, vol. 14, no. 9, pp. 1474-1478, Sept. 2017, DOI: 10.1109/LGRS.2017.2714184.

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科研成果

智能安防监控系统

团队针对安防监控视频大数据应用中，异常事件监测及预警的自动化、智能化、实时化等需求，利用基于深度学习的目标检测、目标识别、目标跟踪、姿态检测、人群密度检测等算法，结合本校实测安防监控视频大数据，在传统的监控系统上进行二次开发，设计实现了具有异常跟踪检测、跌倒检测、奔跑检测、违禁区域闯入检测、打架检测、人群密度预警等功能的智能安防监控系统，极大的减少了安防所需的人力物力，提升了异常事件的处理效率，并可在一定程度上避免危险事件发生。对智慧校园、安全校园的建设起到重要作用。