Yang Shunkun, Beihang University Blue Sky Distinguished Professor and Doctoral Supervisor; National-Level Leading Talent; National-Level Young Talent; Director/Chief Scientist of the Trustworthy AI Systems Laboratory; Deputy Director of the Beihang Reliability Management and Testing Center for AVIC Computer Software; Adjunct Professor/Doctoral Supervisor at China Agricultural University (Computer Science and Technology/Artificial Intelligence); Dual-Appointment Professor/Doctoral Supervisor at Hangzhou Beihang International Innovation Institute (Artificial Intelligence/Computer Science/Software Engineering/Electronic Information/Low-Altitude Intelligent Transportation, etc.); Dual-Appointed Professor/Doctoral Supervisor at the United Nations Affiliated Regional Centre for Space Science and Technology Education in Asia and the Pacific (China) (Computer Science/Micro Satellites); State-Sponsored Visiting Scholar at the Department of Computer Science, Columbia University, New York, USA; Associate Editor of IEEE TRANSACTIONS ON RELIABILITY; Researcher at the National Key Laboratory in Reliability; Academic Committee Member of the Beijing Key Laboratory in Power Dispatch Automation; Academic Committee Member of the Beihang School of Reliability; Chair of the International Academic Forum on Dependable Testing of Safety-Critical Systems (DTES); Executive Chair of the Academic Forum on Reliability Science and Engineering of Complex Systems; Beijing Young Elite; Beihang Young Top-Notch Talent; Secretary-General of the CICC Reliability Committee; Outstanding Scientific Worker of the China Electronics Society; Outstanding Contributor of the Chinese Institute of Command and Control.

Representative Academic Papers (Parts):

[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 Reliability, 71(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 Technology, 71(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 Electronics, 69(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 Reliability, 70(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 Reliability, 70(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 Electrification, 7(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. Energy, 191, 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 Sources, 449, 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 Journal, 28, 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 Computing, 116, 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 Safety, 217, 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 Engineering, 25(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 Sciences, 679, 121106.

[21].Wu, M., Yang, S.*, Li, D., Liu L., Bian C. (2025). DCML-CSAR: A Deep Cascaded Framework with Dual-Coupled Memory Learning and Orthogonal Feature Extraction via Recursive Parameter Transfer for SOH-RUL Assessment.  Reliability Engineering & System Safety

[22]. Duan, Z., Bian, C., Yang, S.*, &Li, C.(2025).Prompting large language model for multi-location multi-step zero-shot wind power forecasting. EXPERT SYSTEMS WITH APPLICATIONS, 280, 127436.

Representative Academic Monographs:

[1] Principles and Simulation of Flight Failures, by Yang Shunkun, Yao Qi. (2023)

[2] Complex Network Theory and Intelligent Software Analysis, by Yang Shunkun, Gou Xiaodong, Yang Minghao, Duan Zhiyu, Shao Qi. (2025, funded by the National Science and Technology Academic Publishing Fund)