张军

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Personal Information

Supervisor of Master's Candidates

  • School/Department:

    信息工程学院
  • Gender:

    Male
  • Degree:

    Doctor of Engineering
  • Status:

    On-the-job
  • Teacher College:

    School of Information Engineering

Profile

工学博士,教授,主要研究方向为人工智能、压缩感知理论及应用,大数据的感知、表示与分析,面向可穿戴设备的智能信息处理等。主持包括国家自然科学基金项目在内的多项国家级、省市级科研项目。在IEEE Trans. Signal Proc., IEEE Internet of Things Journal, IEEE Trans. Instrumentation and Meas., IEEE J. Biomedical and Health Infor., IEEE Wireless Comm. Lett.,IEEE Signal Proc. Lett., IEEE Photonics Technology Lett.,Information Science等国际权威期刊上发表科研论文40余篇,曾获广东省自然科学二等奖(2019年,排名第五)、广东工业大学教学成果二等奖(2017年,排名第一)、广东工业大学先进科技工作者等奖励。



学术兼职:

1.IEEE 会员

2.中国计算机学会 人工智能与模式识别专委会 执行委员

3.中国人工智能学会 教育工作委员会 委员

4.广东省科技咨询专家

5.担任下列国际权威期刊审稿人:

IEEE Trans Neural Networks and Learning Systems、IEEE Trans. Fuzzy System、IEEE Trans. Neural Systems and Rehabilitation Engineering、IEEE Trans Industrial Informatics、IEEE Journal of Biomedical and Health Informatics、IEEE Signal Processing Letters, IEEE Communication Letters、Digital Signal Processing、Neural Processing Letters,Neurocomputing、Multidimensional Systems and Signal Processing、Circuits, Systems and Signal Processing等。



主要荣誉:

1. 2019年广东省自然科学二等奖(排名第五)

2. 广东工业大学信息工程学院专业建设贡献奖(2018年)

3. 广东省“千百十工程”校级培养对象

4. 入选首批“广东工业大学优秀青年教师培养计划”

5. 广东工业大学第十届校级教学成果奖二等奖(排名第一)

6. 第十六届全国大学生智能汽车竞赛全国总决赛二等奖 (指导老师)

7.  第七届全国大学生“飞思卡尔”杯智能汽车竞赛华南赛区二等奖 (指导老师)

8. 广东工业大学第一届青年教师研究论文竞赛“十佳研究论文”奖

9. 湖南省优秀毕业生


主要论文:

[1] Luhua Wang and Jun Zhang*, “BPDQ_p-Net: A Deep Unfolding Method for Quantized Compressed Sensing,” IEEE Signal Processing Letters, vol.31, pp: 531-535, 2024 (*Corresponding Author) (中科院2区)

[2] Jun Zhang, Guangfei Xie, Guojun Han, Zhu Liang Yu, Zhenghui Gu and Yuanqing Li, “Compressive Sensing based Power Allocation Optimization for Energy Harvesting IoT Nodes, ” IEEE Trans. Wireless Comm., vol. 21, no. 6, pp: 4535-4548, 2022 (中科院1区)

[3] Ting Li, Jun Zhang*, Zhijing Yang, Zhu Liang Yu, Zhenghui Gu and Yuanqing Li, “Dynamic User Activity and Data Detection for Grant-free NOMA via Weighted L2,1 Minimization, ” IEEE Trans. Wireless Comm., vol. 21, no. 3, pp: 1638 - 1651, 2022. (*Corresponding Author)(中科院1区)

[4] Jun Zhang, Yuanqing Li, Zhu Liang Yu, Zhenghui Gu, Yu Cheng and Huoqing Gong, “Deep Unfolding with Weighted L1 Minimization for Compressive Sensing,” IEEE Internet of Things Journal, vol. 8, no. 4, pp: 3027-3041, 2021.(中科院1区)

[5] Jun Zhang, Urbashi Mitra, GuanWen Huang and Nicolo Michelus. “Support recovery from noisy random measurements via weighted L1 minimization,” IEEE Trans. Signal Proc., vol.66, no.17, pp: 4527 – 4540, 2018(中科院1区)

[6] Jun Zhang, Zhuliang Yu, Ling Cen, Zhenghui Gu, Yuanqing Li and Zhiping Lin, “Deterministic Construction of Sparse Binary Measurement Matrix via Incremental Integer Optimization,” Information Science, 430–431 (2018) , pp: 504–518, 2018(中科院1区)

[7] Jun Zhang, Zhenghui Gu, Zhuliang Yu and Yuanqing Li, “Energy-Efficient ECG Compression on Wireless Biosensors via Minimal Coherence Sensing and Weighted L1 Minimization Reconstruction,” IEEE Journal of Biomedical and Health Informatics, vol.19, no.2, pp: 520-528, 2015(中科院1区)

[8] Jun Zhang, Jiaxin Zhou, Zhenghui Gu, Zhi Zhang, Luhua Wang, Zhu Liang Yu and Yuanqing Li, “CS-LeCT: Chained Secure and Low-Energy Consumption Data Transmission Based on Compressive Sensing,” IEEE Trans. Instrumentation and Measurement, 2023, DOI: 10.1109/TIM.2023.3280495.(中科院2区)

[9] Yu Cheng, Kin-Yeung Wong, Kevin Hung, Weitong Li, Zhizhong Li and Jun Zhang*. “Deep Nearest Class Mean Model for Incremental Odor Classification,” IEEE Trans. Instrumentation and Measurement, vol. 68, no.4, pp: 952-962, 2019 (*Corresponding Author)(中科院2区)

[10] Jun Zhang, Yongping Pan and Jie Xu. “Compressive Sensing for Joint User Activity and Data Detection in Grant-Free NOMA,”IEEE Wireless Communications Letters, vol. 8, no. 3, pp: 857-860, 2019(中科院2区)

[11] Jun Zhang, Zhuliang Yu, Zhenghui Gu, Yuanqing Li and Zhiping Lin. “Multichannel Electrocardiogram Reconstruction in Wireless Body Sensor Networks through Weighted ℓ1,2 Minimization,” IEEE Trans. Instrumentation and Measurement, vol. 67, no. 9, pp: 2024 – 2034, 2018(中科院2区)

[12] Jun Zhang,Guojun Han and Yi Fang, “Deterministic Construction of Compressed Sensing Matrices from Protograph LDPC Codes,” IEEE Signal Processing Letters, vol.22, no.11, pp: 1960-1964, 2015(中科院2区)

[13] Jun Zhang, Zhuliang Yu, Yuanqing Li, Gordon Ning Liu and Zhenghui Gu, “Weighted regularized sparse recovery method for optical power monitoring,” IEEE Photonics Technology Letters, vol.24, no.1, pp: 55-57, 2012(中科院2区)

[14] Jun Zhang, Xieping Gao, Yuanqing Li. “Efficient Wavelet Networks for Function Learning Based on Adaptive Wavelet Neuron Selection,” IET Signal Process.  vol.6, no.2, pp: 79-90, 2012

[15] Jun Zhang, Urbashi Mitra, GuanWen Huang and Nicolo Michelus. “Support recovery from noisy random measurements via weighted L1 minimization,” 2016 IEEE International Symposium on Information Theory (ISIT 2016),Barcelona, Spain.

[16] Jun Zhang, Yuanqing Li, Zhuliang Yu and Zhenghui Gu. “Sufficient conditions for sparse recovery by weighted ℓ1-constrained quadratic programming,” 2016 International Joint Conference on Neural Networks (IJCNN 2016),Vancouver, Canada.

[17] Ronghua Ma, Hao Zhang, Jun Zhang, Xiaoli Zhong, Zhuliang Yu, Yuanqing Li, Tianyou Yu and Zhenghui Gu, “Bayesian uncertainty modeling for P300-based brain-computer interface,” IEEE Trans. Neural Systems and Rehabilitation Engineering, 2023, DOI: 10.1109/TNSRE.2023.3286688.

[18] Ke Liu, Zhu Liang Yu, Wei Wu, Zhenghui Gu, Jun Zhang, Ling Cen, Srikantan Nagarajan and Yuanqing Li, “Bayesian Electromagnetic Spatio-Temporal Imaging of Extended Sources based on Matrix Factorization,” IEEE Trans. Biomedical and Engineering, vol. 66, no. 9, pp: 2457 - 2469, 2019

[19] Xiaofeng Xie,Zhu Liang Yu,Zhenghui Gu,Jun Zhang,Ling Cen,Yuanqing Li, “Bilinerar Regularized Locality Preserving Learning on Riemannian Graph for Motor Imagery BCI,” IEEE Trans. Neural Systems and Rehabilitation Engineering, vol.26, no.3, pp: 698–708, 2018

[20] Y. Pan, J. Zhang and H. Yu, “Model reference composite learning control without persistency of excitation,” IET Control Theory and Applications, vol. 10, no. 16, pp: 1963-1971, 2016


知识产权:

1. 张军、谢广飞,一种能量收集物联网的传感器能量分配方法和装置,中国发明专利,专利号:ZL2021 1 0797661.1

2. 张军、陈佳鑫,一种随机置乱的确定性压缩感知测量装置及方法,中国发明专利,专利号:ZL2020 1 0290163.3

3. 张军、刘忠俊,一种基于压缩感知网络的图像重构方法和装置,中国发明专利,专利号:ZL2022 1 1264253.0

4. 张军、郭智景,一种图像重构方法、装置、设备及介质,中国发明专利,专利号:ZL20231 0169017.9

5. 张军、王庐华,一种基于深度展开网络的量化信号重构方法,中国发明专利,专利号:CN17319656A


科研项目:

1. 国家自然科学基金(面上)项目,能量收集型物联网中基于压缩感知的能量优化调度方法研究、资助期满、主持。

2. 国家自然科学基金(青年)项目,面向无线体域网的压缩感知矩阵优化构造及性能分析、结题、主持。

3. 国家自然科学基金(青年)项目,面向结构健康监测的无源RFID标签天线智能感知关键技术研究、结题、参与。

4. 国家自然科学基金(面上)项目,医学图像的不同工作域下高性能及鲁棒可逆水印的深入研究、结题、参与。

5. 国家自然科学基金(青年)项目,T 波交替的时域检测及心脏猝死的危险分层预测研究、结题、参与。

6. 广东省自然科学基金(重点项目),多维多功能脑机接口算法与系统研究、结题、参与。

7. 广州市科技计划项目,基于压缩感知的移动互联网实时语音通信QoS关键技术研究、结题、主持

8. 广东高校优秀青年创新人才培养计划(育苗工程)项目,基于压缩感知的心脏CT重构方法研究、结题、主持


教学活动:讲授《计算机网络》、《网络编程》、《数据挖掘与融合技术》等本科生课程



Educational Experience

  • 2008.9 to 2012.6

    华南理工大学  | 模式识别与智能系统  | Doctor of Engineering

  • 2002.9 to 2005.6

    湘潭大学  | 计算机软件与理论  | 工学硕士学位

  • 1998.9 to 2002.6

    湘潭大学  | 计算机科学与技术  | 工学学士学位

Work Experience

  • 2015.2 to 2016.2

    南加州大学

  • 2005.7 to Now

    广东工业大学