李沂滨

教授，博士生导师

英国拉夫堡大学博士（2009）

澳门新葡萄老版本8883副教授（2010-2017，2016年5月获博士生指导资格）

澳门新葡萄老版本8883教授（2017-，2019年3月入选“齐鲁青年学者” 支持计划）

研究方向：

智能计算；故障诊断、预测及健康管理；故障诊断系统开发

部分代表性论文:

1.Song, Y; Li, YB*; Jia, L; Qiu, MK. Retraining Strategy based Domain Adaption Network for Intelligent Fault Diagnosis. IEEE Transactions on Industrial Informatics, 2020, 16(9): 6163-6171.

2.Guo, QW; Li, YB*; Song, Y; Wang, DC; Chen, W. Intelligent Fault Diagnosis Method Based on Full 1-D Convolutional Generative Adversarial Network. IEEE Transactions on Industrial Informatics, 2020, 16(3): 2044-2053.

3.Li, YB; Song, Y*; Jia, L*; Gao, SY; Li, QQ; Qiu, MK. Intelligent Fault Diagnosis by Fusing Domain Adversarial Training and Maximum Mean Discrepancy via Ensemble Learning. IEEE Transactions on Industrial Informatics, 2020, Early Access.

4.Song, Y; Gao, SY; Li, YB*; Jia, L*; Li, QQ; Pang FZ. Distributed Attention-Based Temporal Convolutional Network for Remaining Useful Life Prediction. IEEE Internet of Things Journal, 2020, Early Access.

5.Si, J; Li, YB; Ma, SL*. Intelligent fault diagnosis for Industrial big data.Journal of Signal Processing Systems, 2018. 9: 1221–1233.

6.Li, YB; Gai, KK; Qiu, LF; Qiu, MK*. Intelligent cryptography approach for secure distributed big data storage in cloud Computing. Information Science, 2017. 387: 103–115.

7.Li, YB; Chen, M; Dai, WY; Qiu, MK*. Energy optimization with dynamic task scheduling mobile cloud computing.IEEE Systems Journal, 2017. 1: 96-105.

8.Li, YB; Dai WY; Ming Z*；et al. Privacy protection for preventing data over-collection in smart city. IEEE Transactions on Computers, 2016. 5: 1339-1350.

9.Li, YB; Gai KK; Ming Z*; et al. Intercrossed access controls for secure financial services on multimedia big data in cloud systems. ACM Transactions on Multimedia Computing Communications and Applications, 2016. 12: article 67.

10.Li, YB*; Jia, ZP; Li, X. Task scheduling based on weather forecast in energy harvesting sensor systems. IEEE Sensors Journal, 2014. 11: 3763-3765.

11.Li, YB*; Jia, ZP; Xie, S. Dynamically reconfigurable hardware with a novel scheduling strategy in energy-harvesting sensor networks. IEEE Sensors Journal, 2013. 5: 2032-2038.

专利：

[1]宋艳;李沂滨;贾磊;王代超;郭庆稳.一种基于集成域自适应的故障诊断方法及系统:中国,CN202010490493.7[P].2020-10-02.

[2]李新;李沂滨.一种基于知识库的机械设备故障诊断方法和装置:中国,CN201810175974.1[P].2020-08-18.（已授权）

[3]李沂滨;张天泽;贾磊;宋艳;王代超;高辉;胡晓平.基于时序差分更新经验回放缓存的路径规划方法及系统:中国,CN202010115628.1[P].2020-06-30.

[4]李沂滨;胡晓平;高辉;宋艳;张天泽;王代超.基于卷积神经网络代价敏感学习的故障诊断方法及系统:中国, CN202010115610.1 [P].2020-06-26.

[5]宋艳;李沂滨;高辉;胡晓平;王代超;张天泽.基于DA-TCN的设备剩余使用寿命的估计方法及系统:中国, CN202010107734.5 [P].2020-06-26.

[6]李沂滨;王代超;贾磊;高辉;宋艳;张天泽;胡晓平.基于多尺度信息融合的轴承故障诊断方法及系统:中国, CN202010112157.9 [P].2020-06-12.

[7]李沂滨;高辉;胡晓平;王代超;宋艳;张天泽;郭庆稳.一种机械设备剩余使用寿命预测方法及系统:中国,CN202010115620.5[P].2020-06-12.

[8]李沂滨;宋艳;郭庆稳;王代超.一种面向机电设备的智能故障诊断方法及系统:中国,CN201911000874.6[P].2020-06-09.（已授权）

[9]宋艳;李沂滨;何波.基于自适应像素值约束和MRF的声呐图像分割方法:中国,CN201811474946.6[P].2019-05-21.

[10]宋艳;李沂滨;何波.基于SLIC和自适应滤波的声呐图像均衡化方法:中国,CN201811474850.X [P].2019-05-03.

[11]李沂滨;贾智平;谢帅;赵衍恒.基于HOG和SVM的行人检测系统的FPGA架构及其实现方法:中国, CN201310053625.X [P].2016-01-20.（已授权）

[12]李沂滨;贾智平;李新;陈仁海;陈健.AES加密算法中列混淆过程指令优化方法及其指令集处理器:中国, CN201110024639.X [P].2011-06-01.（已授权）

个人简介：

李沂滨，男，澳门新葡萄老版本8883教授。现任中国计算机学会会员、IEEE会员、计算机学会体系结构专委会专委。

近年来，在理论研究方面，围绕无线传感网、CPS、物联网等系统中的关键技术问题展开研究，如基于深度学习方法的故障诊断、能耗及计算约束下的安全计算、多媒体数据中的认证问题、能量采集环境下的任务调度等问题。并将这些理论研究与具体的应用场景如故障诊断、智慧城市、金融认证等相结合展开研究。近五年以第一作者发表论文27余篇，研究成果以第一作者发表在 IEEE Transactions on Computer (TC)、IEEE Transactions on Industrial Informatics（TII）、IEEE Internet of Things (IoT)Journal、IEEE Transactions on Sustainable Computing (T-SUSC)、ACM Transactions on Multimedia Computing Communications and Applications（TOMM）、IEEE Transactions on Cloud Computing (TCC)、Information Science(IF)、IEEE Systems Journal、IEEE Sensors Journal等国际顶级或主流学术杂志。近五年以第一作者发表论文，他引 533次（Google Scholar），SCI他引144次，入选 ESI高被引论文1篇，并已获19位IEEE Fellow的正面引用。

在工程实践方面，还积极将研究成果与工程实践相结合。相关研究工作连续得到科技部、总装备部、海军装备部、国家海洋局的项目支持。近5年共主持国家级项目5项。针对我国海洋力量在走向深蓝过程中装备可靠性、水下隐蔽性不足的问题，成功开发了多通道状态监测及故障诊断系统，已进入应用推广阶段。

Prof. Yibin Li, Male, Professor of Shandong University. He is CCF (China Computer Federation) member, IEEE (Institute of Electrical and Electronics Engineers) member, the Committee on the architecture of the Computer Society (CCF) member.

His research interests cover several different areas of computing, such as deep learning based fault diagnosis, secure computing under energy constraints, secure computing for multimedia data, task scheduling under energy harvesting environment. These researches have been adopted in many real-world scenarios such as machinery fault diagnosis, smart city, financial computing. During past five years, Prof. Li has published more than 20 papers in many top journals including IEEE Transactions on Computer (TC), IEEE Transactions on Industrial Informatics（TII), IEEE Internet of Things （IoT）Journal，IEEE Transactions on Sustainable Computing (T-SUSC), ACM transactions on multimedia Computing Communications and Applications (ToMM), IEEE Transactions on Cloud Computing (TCC), Information Science (IF), IEEE Systems Journal, and IEEE Sensors journal. Currently, these papers have been cited more than five hundred times (Google Scholar). The most cited paper has been cited more than one hundred times (published in 2016) which is also listed as ESI High cited paper (top 1%). His research has been continuously supported by The Ministry of Science and Technology, the General Equipment Department of Military, Naval Equipment Development Department.