教育/工作经历：

2025.07-至今　　 开云kaiyun官网，开云kaiyun官网，特聘副教授

2024.07-2025.06　北京航空航天大学，国际前沿交叉科学研究院，助理教授/博士后

2023.01-2024.12　香港理工大学，机械工程系，香江学者研究员/博士后

2020.11-2024.06　北京航空航天大学，航空发动机研究院，助理研究员/博士后

2016.09-2020.07　北京航空航天大学，航空宇航推进理论与工程，获博士学位

代表性论著:

[1] LK Song, F Tao, et al. Cascade sampling-driven block mapping for coupled reliability evaluation of turbine cooling systems, Mechanical Systems and Signal Processing, 2025.

[2] LK Song, F Tao, et al. Physics-embedding multi-response regressor for time-variant system reliability assessment, Reliability Engineering and System Safety, 2025, 263: 111262.

[3] LK Song, XQ Li, et al. Cascade ensemble learning for multi-level reliability evaluation, Aerospace Science and Technology, 2024, 148: 109101. (ESI 1%高被引论文)

[4] LK Song, YS Choy, et al. Multi-XGB: A multi-objective reliability evaluation approach for aeroengine turbine discs, Digital Engineering, 2024, 2: 100006.

[5] LK Song, GC Bai, et al. A unified fatigue reliability-based design optimization framework for aircraft turbine disk, International Journal of Fatigue, 2021, 152: 106422.

[6] LK Song, GC Bai, et al. A novel metamodeling approach for probabilistic LCF estimation of turbine disk, Engineering Failure Analysis, 2021, 120: 105074.

[7] LK Song, GC Bai, et al. Dynamic surrogate modeling approach for probabilistic creep-fatigue life evaluation of turbine disks, Aerospace Science and Technology, 2019, 95: 105439.

[8] LK Song, GC Bai, et al. Probabilistic LCF life assessment for turbine discs with DC strategy-based wavelet neural network regression, International Journal of Fatigue, 2019, 119, 204-219.

[9] LK Song, GC Bai, et al. Multi-failure probabilistic design for turbine bladed disks using neural network regression with distributed collaborative strategy, Aerospace Science and Technology, 2019, 92: 464-477.

[10] LK Song, J Wen, et al. Distributed collaborative probabilistic design of multi-failure structure with fluid-structure interaction using fuzzy neural network of regression, Mechanical Systems and Signal Processing, 2018, 104: 72-86.

[11] LK Song, CW Fei, et al. Dynamic neural network method-based improved PSO and BR algorithms for transient probabilistic analysis of flexible mechanism, Advanced Engineering Informatics, 2017, 33: 144-153.

[12] LK Song, CW Fei, et al. Multi-objective reliability-based design optimization approach of complex structure with multi-failure modes, Aerospace Science and Technology, 2017, 64: 52-62.

[13] YW Wang, LK Song*, et al. Probabilistic fatigue estimation framework for aeroengine bladed discs with multiple fuzziness modeling, Journal of Materials Research and Technology, 2023, 24: 2812-2827.

[14] XQ Li, LK Song*, et al. Multivariate ensembles-based hierarchical linkage strategy for system reliability evaluation of aeroengine cooling blades, Aerospace Science and Technology, 2023, 138: 108325. (ESI 0.1%热点论文 & ESI 1%高被引论文)

[15] BW Wang, WZ Tang, LK Song*, et al. Deep neural network-based multiagent synergism method of probabilistic HCF evaluation for aircraft compressor rotor, International Journal of Fatigue, 2023, 170: 107510.

[16] XQ Li, LK Song*, et al. Vectorial surrogate modeling approach for multi-failure correlated probabilistic evaluation of turbine rotor, Engineering with Computers, 2023, 39(3): 1885-1904. (ESI 1% 高被引论文)

[17] H Zhang, LK Song*, et al. Active extremum Kriging-based multi-level linkage reliability analysis and its application in aeroengine mechanism systems, Aerospace Science and Technology, 2022, 131: 107968.

[18] K Deng, LK Song*, et al. Improved Kriging-based hierarchical collaborative approach for multi-failure dependent reliability assessment, International Journal of Fatigue, 2022, 160: 106842.

授权发明专利:

[1] 陶飞, 宋鲁凯, 王子同, 张贺, 左颖. 一种航空发动机叶盘结构可靠性数实融合测试方法[P]. 202411752671.3

[2] 陶飞, 王思远, 宋鲁凯, 周尧明, 张贺, 左颖. 一种面向整体叶盘加工的刀具磨损数实融合测试方法[P]. 202510546237.8

[3] 陶飞, 张帅, 宋鲁凯, 张贺, 左颖, 朱永怀. 基于数字空间密度网格的多传感融合人机距离估计方法[P]. 202510181396.2

[4] 陶飞，张贺，张帅，宋鲁凯, 王子同. 一种空天装备数实试验数据匹配与映射方法、装置[P]. 202411919720.8

[5] 宋鲁凯, 白广忱, 张红, 李雪芹. 一种航空发动机典型机构多构件失效相关的可靠性仿真方法[P]. CN202210209702.5

[6] 宋鲁凯, 白广忱, 李雪芹, 张红, 罗安平. 一种基于学科分解的多失效结构分布式协同可靠性方法[P]. CN202210084456.5

[7] 宋鲁凯, 白广忱, 李雪芹, 张红, 马心怡. 一种基于多层级分布式协同代理模型的复杂结构可靠性方法[P]. CN202210175261.1

[8] 宋鲁凯, 白广忱, 张红, 李雪芹, 樊晨辉. 一种基于多目标代理模型的静叶调节机构系统可靠性分析方法[P]. CN202111668038.2

成果与荣誉：

特聘副教授，人社部香江学者，从事数智装备可靠性数字孪生相关研究。主持国家自然科学基金、省自然科学基金、博士后自然科学基金、卓越学术基金等项目，作为项目骨干参与国家重点研发、XX重大专项、自然科学基金（区域联合、重点、面上）等项目。获香江学者奖、航空强国中国心奖、Early Career Award等荣誉，2023、2024连续入选World’s Top 2% Scientists榜单。