代明军(Mingjun Dai)

男，博士，教授，博士生导师，深圳市海外高层次人才（孔雀计划B类人才），深圳市高层次人才（后备级人才），南山区B类领航人才，加拿大滑铁卢大学访问学者。2012年于香港城市大学获得博士学位并在深圳大学工作。研究兴趣包括分布式深度学习(联邦学习)、分布式计算、无线通信网、云存储（分布式存储）中网络编码设计、车联网等多个方面。主持科研项目包括国家重点研发计划、国家自然科学基金面上及青年、教育部博士点基金、广东省自然科学基金、省教育厅基金、西电国家重点实验室开放课题、深圳孔雀创新基金、深圳高端人才启动基金、腾讯犀牛鸟基金等。

Mingjun Dai, male, Professor.

研究兴趣：

分布式深度学习(联邦学习)、分布式计算、分布式存储、无线通信网、低复杂度算法、人工智能与编码结合

Research interests: Distributed deep learning (federated learning), coded distributed computing, distributed storage, wireless communication network, low complexty algorithm, combination of artificial intelligence and coding.

教授课程：

通信原理；数字信号处理；微型计算机技术；网络编码；C语言程序设计；可视化计算语言；无线网络技术等

研究生招生方向：

学术型博士：信息与通信工程

专业型博士：电子信息

学术型硕士：信息与通信工程

专业型硕士：通信工程

Research student recruitment: 

PhD candidate: distributed deep learning (federated learning), information and communication.

Mphil candidate: distributed deep learning (federated learning), information and communication, electronics and communication.

招聘需求：

博士后，方向为分布式深度学习(联邦学习)、通信编解码、深度学习等。

Recruitment:

Postdoc in distributed deep learning (federated learning), distributed computing, encoding/decoding in communication.

近年主持科研项目清单：

1.国家重点研发计划政府间重点专项项目(2023YFE0126800, 面向AI和合作机器人制造收敛的去中心化联邦学习)，在研

2.国家自然科学基金面上项目(62071304, 面向编码分布式计算的低复杂度实数编解码算法研究)，在研

3.国家自然科学基金国际(地区)合作与交流项目(62411560164, 面向物联网边缘的联邦学习超参数调节)，已结题

4.国家自然科学基金青年项目(61301182,广义线性索引编码研究)，已结题

5.广东省自然科学基金面上项目(2024A1515010625,自调参高速及高准确率联邦训练研究)，在研

6.广东省自然科学基金面上项目(2020A1515010381，二进制纠删码分布式存储系统的编解码及私有信息检索设计)，已结题

7.广东省自然科学基金自由申请(2018A0303130131，基于二进制锯齿解码的分布式存储系统关键技术研究)，已结题

8.深圳市自然科学基金(20200826152915001，低复杂度的编码分布式计算)，已结题

9.教育部博士点基金(20134408120004,带有编码缓存和请求的线性索引编码及应用研究)，已结题

10.西安电子科技大学国家重点实验室(ISN)开放基金(ISN18-17,低复杂度解码在存储及通信中设计)，已结题

11.孔雀计划海外高层次人才创新创业专项资金技术创新和创业资助项目（KQCX20140509172609163,软件定义网络平台上基于网络编码和演化博弈的车载自组通信网），已结题

12.西安电子科技大学国家重点实验室(ISN)开放基金(ISN15-06,广义索引编码研究)，已结题

13.广东省教育厅特色创新类项目（自然科学类）(2015KTSCX121,低复杂度解码在分布式云存储中设计)

14.广东省自然科学基金(s2013040016857,带编码边信息和反馈的数据分发机制研究)，已结题

15.广东高校优秀青年创新人才培养计划(s2013LYM_0077,缓存和请求数据是编码情况的线性索引编码研究)，已结题

16.深圳市高端人才科研启动基金（00002501，广义线性索引编码及分布式云存储）

17.腾讯“犀牛鸟”-深圳大学青年教师科研基金(低复杂度解码在分布式云存储及多播通信系统中设计)，已结题

部分SCI期刊论文：

[1] M. Dai, C. W. Sung, and Y. Wang, “Distributed on-off power control for amplify-and-forward relays with orthogonal space-time block code,” IEEE transactions on Wireless Commun., vol. 10, no. 6, pp. 1895-1903, Mar. 2011.

[2] M. Dai, H. Y. Kwan, and C. W. Sung, "Linear network coding strategies for the multiple-access relay channel with packet erasures," IEEE transactions on Wireless Commun., vol. 12, no. 1, pp. 218-227, Jan. 2013.

[3] M. Dai, K. W. Shum, and C. W. Sung, "Data dissemination with side information and feedback," IEEE transactions on Wireless Commun., vol. 13, no. 9, pp. 4708-4720, Sep. 2014.

[4] M. Dai, C. W. Sung, etal, "A new zigzag-decodable code with efficient repair in wireless distributed storage," IEEE transactions on Mobile Comput.,vol. 16, no. 5, pp. 1218-1230, May 2017.

[5] C. W. Sung, M. Dai*, and P. Hu, "Achieving the outage capacity of the diamond relay network to within one bit and even less," IEEE transactions on Veh. Technol., vol. 60, no. 8, pp. 4088-4093, Oct. 2011.

[6] M. Dai and C. W. Sung, “A distributed on-off amplify-and-forward protocol for the fading parallel relay channel,” IEEE Commun. Letters, vol. 13, no. 9, pp. 643-645, Sep. 2009.

[7] M. Dai, S. Zhang, B. Chen, X. Lin, and H. Wang, "A refined convergence condition for iterative waterfilling algorithm," IEEE Commun. Letters, vol. 18, no. 2, pp. 269-272, Feb. 2014.

[8] M. Dai and C. W. Sung, “Achieving high diversity and multiplexing gains in the asynchronous parallel relay network,” Trans. on Emerging Telecommun. Technol. (ETT), vol. 24, no. 2, pp. 232-243, Feb. 2013.

[9] M. Dai, P. Wang, S. Zhang, B. Chen, H. Wang, X. Lin, and C. Sun, "Survey on cooperative strategies for wireless relay channels," Trans. on Emerging Telecommun. Technol. (ETT), vol. 25, no. 9, pp. 926-942, Sep. 2014.

[10] M. Dai, H. Wang, etal, “Opportunistic relaying with analogue and digital network coding for two-way parallel relay channels," IET Commun., vol. 8, no. 12, pp. 2200-2206, Aug. 2014.

[11] M. Dai, S. Zhang, etal, "Network-coded relaying in multiuser multicast D2D network," International Journal of Antennas and Propogation, vol. 2014, ArticleID 58794, pp. 1-7, 2014.

[12] M. Dai, D. Liu, Y. Fan, etal, "Evolutionary study on mobile cloud computing," Neural Comput. & Applications, vol. 28, no. 9, pp. 2735-2744, 2017.

[13] M. Dai, B. Mao, D. Shen, etal, "Incorporating D2D to Current Cellular Communication System," Mobile Information Systems, vol. 2016, 2732917, pp. 1-7, Mar. 2016.

[14] R. Feng, M. Dai*, etal, "Linear precoding for multiuser visible-light communication with field-of-view diversity," IEEE Photonics Journal, vol. 8, no. 2, ArticleID 7902708, Apr. 2016.

[15] M. Dai, Z. Lu, etal, "Design of (4, 8) binary code with MDS and zigzag-decodable property," Wireless Personal Communications,vol. 89, no. 1, pp. 1-13, Jul.2016.

[16] M. Dai, J. Yuan, etal, "A power allocation method for 2×2 VLC-MIMO indoor communication," Optical Review,vol. 23, no. 4, pp. 678-682, Aug. 2016.

[17] J. Zhong, Y. F. Feng, M. Dai, "A biologically inspired improvement strategy for particle filter: Ant colony optimization assisted particle filter," International Journal of Control Automation and Systems,vol. 8, no. 3, Jun. 2010.

[18] R. Feng, M. Dai*, and H. Wang, "Distributed beamforming in MISO SWIPT system," IEEE transactions on Veh. Technol., vol. 66, no. 6,pp. 5440-5445, Jun. 2017.

[19] F. Ding, H. Wang, S. Zhang, and M. Dai, "Multiuser untrusted relay networks with joint cooperative jamming and opportunistic scheduling under perfect and outdated CSI," Electronics Letters, vol. 52, no. 23, pp. 1925-1927, Nov. 2016.

[20] M. Dai, S. Zhang, H. Wang, S. Jin, "A low storage room requirement framework for distributed ledger in blockchain," IEEE Access, vol. 6, no. 3, pp. 22970-22975, Mar. 2018.

[21] M. Dai, B. Mao, X. Gong, C. W. Sung, W. Zhuang, X. Lin, "Zigzag-division multiple access for wireless networks with long and heterogeneous delays," IEEE transactions on Aerospace and Electronic Systems, vol. 55, no. 6, pp. 2822-2835, Dec. 2019.

[22] M. Dai, Z. Zheng, et al, "SAZD: A low computational load coded distributed computing framework for IoT systems," IEEE Internet of Things Journal, vol. 7, no. 4, pp. 3640-3649, Apr. 2020.

[23] Z. Zhang, K. Zhang, Z. Peng, D. Zeng, and M. Dai, "Velocity analysis of BP decoding waves for SC-LDPC ensembles on BMS channels: An interpolation-based approach," IEEE transactions on Commun., vol. 68, no. 6, pp. 3286-3301, Jun. 2020.

[24] M. Dai, H. Deng, et al, "Design of binary erasure code with triple simultaneous objectives for distributed edge caching in industrial internet of things networks," IEEE transactions on Industrial Informatics, vol. 16, no. 8, pp. 5497-5504, Aug. 2020.

[25] M. Dai, S. Lu, et al, "Error correction CP-BZD storage codes for content delivery in drive-thru internet," IEEE transactions  on Intelligent Transportation Sys.,vol. 21, no. 11, pp. 4869-4882, Nov. 2020.

[26] M. Dai, Z. Zheng, et al, "Edge Computing-Aided Coded Vertical Federated Linear Regression," IEEE transactions on Cognitive Communications and Networking,vol. 8, no. 3, pp. 1543-1551, Sep. 2022.

[27] M. Dai, Z. Zhang, et al, "PID controller-based adaptive gradient optimizer for deep neural networks," IET Control Theory & Applications,vol. 17, pp. 2032-2037, Nov. 2022.

[28] M. Dai, J. Yuan, et al, "Distributed encoding and updating for SAZD coded distributed training," IEEE transactions on Parallel and Distributed Systems,vol. 34, no. 7, pp. 2124-2137, Jul. 2023.

[29] M. Dai, Z. Zhang, et al, "2D-SAZD: A novel 2D coded distributed computing framework for matrix-matrix multiplication," IEEE transactions  on Services Computing,vol. 17, no. 3, pp. 705-717, Jun. 2024.

[30] S. Li, M. Dai*, et al, "MMPC-Net: Multi-Granularity and Multi-Scale Progressive Contrastive Learning Neural Network for Remote-Sensing Image Scene Classification," IEEE GeoScience and Remote Sensing Letters,vol. 21, pp. 1-5, May 2024.

[31] M. Dai, J. Zhang, et al, "Real Field Error Correction for Coded Distributed Computing based Training," to appear in IEEE transactions on Cognitive Communications and Networking, 2024.

部分会议论文：

[1] K. Zhang, M. Dai, D. Zeng, Z. Zhang, “Decoding wave velocity analysis for SC-LDPC ensembles on BMS channels using interpolation,”Proc. Int. Symp. on Wireless Commun. Sys. (ISWCS), pp. 32-37, Nov. 2019.

[2] M. Dai,S. Huang, J. Zhong,and et al, "Influence of noise on transfer learning in Chinese sentiment classification using GRU,"Int. Conf. On Natural Comput., Fuzzy Sys. And Knowledge Discovery, Guilin, China, Jul. 2017.

[3] J. Zhong,R. Novianto, M. Dai,and et al, "A hierarchical emotion regulated sensormotor model: Case studies,"Control and Decision Conf., pp. 4965-4970, Yinchuan, China, May 2016.

[4] M. Dai, Y. Kong,and et al, "A fully distributed training for class incremental learning in multihead networks," IEEE Infocom Conf.(PerAI-6G), Jan. 2023.

[5] M. Dai, G. Xu, and et al, "PID controller-based adaptive federated learning," IEEE ICCC, Aug. 2024.

[6] S. Kianoush, A. Minora, S. Savazzi, M. Dai, "A Federated Learning Approach For Operator Monitoring in Heterogeneous Cobot Environments," IEEE  International Conference on Emerging Technologies and Factory Automation Conf. (ETFA),  2024.

学术服务：

Associate Editor: Internet Technology Letters

办公室(office)：N905

办公电话(Telephone no.)：+86-755-86960983

E-mail：mjdai@szu.edu.cn