杨顺昆

教授

硕士生导师

博士生导师

个人信息

电子邮箱: 入职时间:2003-04-01 所在单位:可靠性与系统工程学院 学历:博士研究生 办公地点:为民楼412 性别:男 联系方式:82338973 学位:工学博士学位 在职信息:在职 主要任职:中航工业计算机软件北航可靠性管理与测评中心副主任 毕业院校:北京航空航天大学

个人简介

杨顺昆,教授、博导;国家级领军人才;国家级青年人才;智能系统可信性实验室主任/首席科学家;中国航空工业计算机软件北航可靠性管理与测评中心副主任;中国农业大学兼职教授/博导(计算机科学与技术/人工智能);美国纽约哥伦比亚大学计算机系访问学者;IEEE TRANSACTIONS ON RELIABILITY期刊编委(Associate Editor可靠性领域国家级重点实验室研究员;电力调度自动化领域北京市重点实验室学术委员会委员;北航可靠性学院学术委员会委员;安全关键系统可信测评国际学术论坛(DTES)主席;复杂系统可靠性科学与工程学术论坛执行主席;北京市青年英才;北航青年拔尖人才;CICC可靠性专委会总干事;中国电子学会优秀科技工作者;中国指挥与控制学会优秀工作者;中国现场统计研究会可靠性分会常务理事。


长期从事信息物理系统可靠性与安全性、复杂软件系统设计分析与测试验证、嵌入式系统仿真建模与加速测试、可信AI与智能测评等基础性研究和工程应用研究。在深度学习与大模型、群体智能与演化计算、形式化验证与概率模型检测、物联网与云计算、复杂网络与渗流理论等前沿技术方法方面取得多项标志性成果。主持国家自然科学基金等多项国家级、省部级科研课题和重大工程任务。在IEEE TRel、TSE、TSMC、TIE、TTE、TVT等国内外学术期刊或会议上发表SCI/EI学术论文100余篇;授权国内外发明专利70余项(美国发明专利4项);软件著作权25项;出版专著两部;获省部级/国家一级学会等科技奖励8项,其中一等奖4项(2项排名1)。研究成果在航空、航天、船舶、高铁、汽车、电网、新能源、发动机、电子、通信、智能制造、工业软件等领域广泛应用。


代表性学术论文(部分):

[1].Yang, M., Yang, S.*, & Wong, W. E. (2024). Multi-objective Software Defect Prediction via Multi-source Uncertain Information Fusion and Multi-task Multi-view Learning. IEEE Transactions on Software Engineering.

[2].Bian, C., Han, X., Duan, Z., Deng, C., Yang, S.*, & Feng, J. (2024). Hybrid prompt-driven large language model for robust state-of-charge estimation of multi-type li-ion batteries. IEEE Transactions on Transportation Electrification.

[3].Gou, X., Zhang, A., Wang, C., Liu, Y., Zhao, X., & Yang, S.* (2024). Software fault localization based on network spectrum and graph neural network. IEEE Transactions on Reliability.

[4].Bian, C., Yang, S.*, Xu, Q., & Feng, J. (2023). Holistic Transmission Performance Prediction of Balise System With Gate-Steered Residual Interweave Networks. IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[5].Yang, S., Gou, X., Yang, M., Shao, Q., Bian, C., Jiang, M., & Qiao, Y. (2022). Software bug number prediction based on complex network theory and panel data model. IEEE Transactions on Reliability71(1), 162-177.

[6].Bian, C., Yang, S.*, Xu, Q., & Meng, J. (2022). Disturbances prediction of bit error rate for high-speed railway Balise transmission through persistent state map**. IEEE Transactions on Vehicular Technology71(5), 4841-4850.

[7].Bian, C., Yang, S.*, Xu, Q., & Meng, J. (2021). Speed adaptability assessment of railway Balise transmission module using a deep-adaptive-attention-based encoder–decoder network. IEEE Transactions on Industrial Electronics69(4), 4195-4204.

[8].Shao, Q., Yang, S.*, Bian, C., & Gou, X. (2020). Formal analysis of repairable phased-mission systems with common cause failures. IEEE Transactions on Reliability70(1), 416-427.

[9].Shao, Q., Yang, S.*, & Gou, X. (2020). Formal analysis of multiple-cell upset failure based on common cause failure theory. IEEE Transactions on Reliability70(4), 1495-1509.

[10].Bian, C., Yang, S.*, & Miao, Q. (2020). Cross-domain state-of-charge estimation of Li-ion batteries based on deep transfer neural network with multiscale distribution adaptation. IEEE Transactions on Transportation Electrification7(3), 1260-1270.

[11].Bian, C., He, H., & Yang, S.* (2020). Stacked bidirectional long short-term memory networks for state-of-charge estimation of lithium-ion batteries. Energy191, 116538.

[12].Bian, C., He, H., Yang, S.*, & Huang, T. (2020). State-of-charge sequence estimation of lithium-ion battery based on bidirectional long short-term memory encoder-decoder architecture. Journal of Power Sources449, 227558.

[13].Shao, Q., Gou, X., Huang, T., & Yang, S.* (2020). Anti-aging analysis for software reliability design modes in the context of single-event effect. Software Quality Journal28, 221-243.

[14].Bian, C., Yang, S.*, Liu, J., & Zio, E. (2022). Robust state-of-charge estimation of Li-ion batteries based on multichannel convolutional and bidirectional recurrent neural networks. Applied Soft Computing116, 108401.

[15].Yang, S.*, Shao, Q., & Bian, C. (2022). Reliability analysis of ensemble fault tolerance for soft error mitigation against complex radiation effect. Reliability Engineering & System Safety217, 108092.

[16].Yang, S.*, Li, H., Gou, X., Bian, C., & Shao, Q. (2022). Optimized Bayesian adaptive resonance theory map** model using a rational quadratic kernel and Bayesian quadratic regularization. Applied Intelligence, 1-16.

[17].Yang, M., Yang, S.*, & Bian, C. (2024). Software Reliability Prediction by Adaptive Gated Recurrent Unit‐Based Encoder‐Decoder Model With Ensemble Empirical Mode Decomposition. Software Testing, Verification and Reliability, e1895.

[18].Bian, C., Duan, Z., Hao, Y., Yang, S.*, & Feng, J. (2024). Exploring large language model for generic and robust state-of-charge estimation of Li-ion batteries: A mixed prompt learning method. Energy, 131856.

[19].Duan, Z., Yang, S.*, Shao, Q., & Yang, M. (2024). PEGA: probabilistic environmental gradient-driven genetic algorithm considering epigenetic traits to balance global and local optimizations. Frontiers of Information Technology & Electronic Engineering25(6), 839-855.

[20].Yao, Q., Yang, S.*, Shao, Q., Bian, C., & Wu, M. (2024). Topological clustering particle swarm optimizer based on adaptive resonance theory for multimodal multi-objective problems. Information Sciences679, 121106.





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