个人简历

工学博士，副教授，硕士生导师，广东省高等学校“千百十工程”校级培养对象，首批“广东工业大学优秀青年教师培养计划”培养对象。主要研究方向为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 Trans. Instrumentation and Measurement, IEEE J. Biomedical and Health Informatics, IEEE Wireless Communications Letters，IEEE Signal Proc. Letters, IEEE Photonics Technology Letters，Information Science等国际权威期刊上发表科研论文20余篇。2014年获得广东工业大学先进科技工作者奖。

学科领域：
科学学位：信息与通信工程
专业学位：电子与通信工程

教育背景：
2008/09 – 2012/06，华南理工大学，模式识别与智能系统专业，博士
2002/09 – 2005/06，湘潭大学，计算机软件与理论专业，硕士
1998/09 – 2002/06，湘潭大学，计算机科学与技术专业，学士

工作经历：
2005/7-至今，广东工业大学，信息工程学院，讲师、副教授
2015/02-2016/02，美国南加州大学(USC)，电子工程系，博士后研究员

主要荣誉：
1. 广东省“千百十工程”校级培养对象
2. 入选首批“广东工业大学优秀青年教师培养计划”
3. 广东工业大学第十届校级教学成果奖二等奖（排名第一）
4. 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）
5. 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
6. 湖南省优秀毕业生

知识产权：
张军、杜佳梦、邹晓瑜. “一种压缩感知的编解码方法、装置、设备及存储介质”，中国发明专利，实审(公开号：CN108199719A)

科研项目：
1. 国家自然科学基金项目，面向无线体域网的压缩感知矩阵优化构造及性能分析、2015/01-2017/12、25万元、结题、主持。
2. 国家自然科学基金项目，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、2018/01-2020/12、22万元、在研、参与。
3. 国家自然科学基金项目，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、2016/01-2019/12、72万元、在研、参与。
4. 国家自然科学基金项目，T 波交替的时域检测及心脏猝死的危险分层预测研究、2010/01-2012/12、20万元、结题、参与。
5. 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、2012/01-2017/12、30万元、结题、参与。
6. 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、2018/04-2020/03，20万元，在研、主持
7. 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、2012/12-2014/12、3万元，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

研究领域

l 压缩感知理论及其应用；
l 网络大数据的感知、表示与分析；
l 面向可穿戴设备的新型感知前端设计""

近期论文

[1] Jun Zhang (张军), 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
[2] Jun Zhang (张军), 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
[3] Jun Zhang (张军), 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
[4] Yu Cheng, Kin-Yeung Wong, Kevin Hung, Weitong Li, Zhizhong Li and Jun Zhang* (张军). “Deep Nearest Class Mean Model for Incremental Odor Classification,” IEEE Trans. Instrumentation and Measurement, 2018, DOI: 10.1109/TIM.2018.2863438 (*Corresponding Author)
[5] Zhenghui Gu, Gang Yan, Jun Zhang* (张军), Yuanqing Li and Zhu Liang Yu. “Automatic Epilepsy Detection based on Wavelets Constructed from Data,” To appear in IEEE Access, 2018 (*Corresponding Author)
[6] Jun Zhang (张军), Yongping Pan and Jie Xu. “Compressive Sensing for Joint User Activity and Data Detection in Grant-Free NOMA,”IEEE Wireless Communications Letters, 2019, DOI: 10.1109/LWC.2019.2897552
[7] Jun Zhang (张军), 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
[8] Jun Zhang (张军)，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
[9] Jun Zhang (张军), Yuanqing Li, Zhuliang Yu et. al, “Recoverability Analysis for Modified Compressive Sensing with Partially Known Support，” PLoS ONE, vol.9, no.2, e87985, doi:10.1371/journal.pone.0087985, 2014
[10] Jun Zhang (张军), 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
[11] Jun Zhang (张军), 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
[12] Jun Zhang (张军), “A comparative study of non-separable wavelet and tensor-product wavelet in image compression，” CMES：Computer Modeling in Engineering & Science, vol.22, no.2, pp: 91-96, 2007
[13] Jun Zhang (张军), Yuanqing Li, Zhuliang Yu and Zhenghui Gu. “Noisy sparse recovery based on parameterized quadratic programming by thresholding，” EURASIP Journal on Advances in Signal Process., vol.2011, Article ID 528734, 7 pages, DOI:10.1155/2011/528734.
[14] Jun Zhang (张军), Yuanqing Li, Zhuliang Yu and Zhenghui Gu. “Effect of Errors in Partially Known Support on the Recoverability of Modified Compressive Sensing、” EURASIP Journal on Advances in Signal Process., vol.2012, DOI: 10.1186/1687-6180-2012-199
[15] Y. Pan, J. Zhang (张军) 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
[16] Xiaofeng Xie，Zhu Liang Yu，Zhenghui Gu，Jun Zhang (张军)，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
[17] Ke Liu, Zhu Liang Yu, Wei Wu, Zhenghui Gu, Jun Zhang (张军), Ling Cen, Srikantan Nagarajan and Yuanqing Li, “Bayesian Electromagnetic Spatio-Temporal Imaging of Extended Sources based on Matrix Factorization,” IEEE Trans. Biomedical and Engineering, 2018, DOI: 10.1109/TBME.2018.2890291
[18] Jinhong Huang，Zhu Liang Yu，Zhenghui Gu，Jun Zhang (张军)，Ling Cen，“Sparse and Heuristic Extreme Learning Machine for Classifer and Regressor Fusion,” International Journal of Machine Learning and Cybernetics.
[19] Jun Zhang (张军), 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， 口头报告.
[20] Jun Zhang (张军), 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，口头报告.
[21] Jun Zhang (张军), Zhenghui Gu, Yuanqing Li and Xieping Gao. “A sparse infrastructure of wavelet network for regression, ” 2010 International Symposium on Neural Networks (ISNN 2010)， Shanghai, China, 口头报告.
1. IEEE 会员
2.中国人工智能学会教育工作委员会 委员
3. 全国高等学校计算机基础教育研究会 智能技术应用专委会 常务委员
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 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。