金士杰，男，副教授，博士/硕士研究生导师，大连市青年才俊。2014年毕业于中国科学院声学研究所，同年进入大连理工大学。瞄准航空航天、储能工程、核工程等国家关注领域重大需求，开展面向材料的无损表征与评价研究，为关键零/部/构件缺陷检测及质量控制提供原理和技术支撑。研究成果已应用于C919大飞机与CZ系列火箭关键功能零部件、“华龙一号”全球首堆与海外首堆等10座核电机组。
        连续主持国家自然科学基金面上/青年基金项目3项，骨干参与国家重点研发计划、“973计划”等国家级/省部级项目10余项，主持和参与企业委托项目近30项；在Mechanical Systems and Signal Processing‌、NDT&E International、Measurement、机械工程学报、航空学报等国内外高水平期刊发表学术论文110余篇，其中SCI/EI收录70余篇；授权中国/美国发明专利30余项，软件著作权5项；获得辽宁省技术发明一等奖、中国核能行业协会科学技术二等奖、辽宁省教学成果三等奖等荣誉；现任中国声学学会检测声学分会委员、中国机械工程学会无损检测分会超声专业委员会委员；《机械工程学报》首届青年编委、《材料工程》与《航空材料学报》第二、三届青年编委；中国机械工程学会高级会员、中国声学学会会员、国家自然科学基金同行评议专家；指导的研究生获得辽宁省优秀毕业生、大连理工大学优秀硕士论文等荣誉。
        团队氛围良好、经费充足、就业途径广。欢迎具有材料、机械、物理、电信、数学、计算机或仪器仪表等交叉背景，脚踏实地并有志于科学研究的同学加入！

       主要研究方向：

       （1）超声信号/图像分析与处理

（2）材料/结构表界面完整性智能化评价

（3）高性能电池损伤表征与寿命评估

（4）数字化无损检测软/硬件系统研发与工程应用

       近三年部分代表性成果（加*为通讯作者）：

[1] Jin S J, Feng W L, et al. Eliminating artifacts in ultrasonic HSTFM imaging of curved components using improved weighted filtering (IWF)[J]. IEEE Sensors Journal. 2026, 26(8): 12544-12552.

[2] Jin S J, Huangfu S Y, et al. Generalized ultrasonic TOFD techniques for detecting axial defects in pipelines[J]. Journal of Nondestructive Evaluation. 2026, 45: 53.

[3] Jin S J, Xing X Y, et al. Identification of fatigue cracks in aluminum alloys based on back propagation neural network[J]. Russian Journal of Nondestructive Testing. 2026, 62(5): 633-648.

[4] Li X, Jin S J*, et al. Efficiency optimization of frequency-domain ultrasonic imaging by adaptive Var-MRLA sparse method[J]. Measurement. 2026, 258: 119181.

[5] Li F Z, You Z J, Jia R M, Jin S J*, Luo Z B*. Phase-delay inversion imaging of low-velocity impact damage in CFRP laminates based on ultrasonic guided wave[J]. Mechanical Systems and Signal Processing‌. 2026, 258: 114662.

[6] Li F Z, You Z J, Jia R M, Jin S J*, Luo Z B*. Modeling of impact damage and guided-wave propagation in CFRP laminates[J]. International Journal of Mechanical Sciences. 2026, 319: 111580.

[7] Zhang X Y, Liu Z H, Kang J L, Jin S J*, Luo Z B*. Evaluation of hygrothermal aging damage in CFRP by machine learning-based multimodal ultrasonic features[J]. Polymer Degradation and Stability. 2026, 244: 111793.

[8] Luo Z B, Bian W S, Liu H H, Wang Y, Jin S J*, Liu X Y*. Cyclic damage of z2cnd18.12n austenitic stainless steel: effects of grain size[J]. Materials Science and Engineering: A. 2026, 968: 150451.

[9] Jin S J, Wang Z C, et al. Applicability and applications of alternative TOFD techniques[J]. Ultrasonics. 2025, 148: 107563.

[10] Jin S J, Su J K, et al. Quantitative detection of axial defects in pipelines based on modified multi-mode total focusing method (MTFM)[J]. Applied Acoustics. 2025, 228: 110288.

[11] Xiong Z H, Chen Y*, Cheng Y S, Lu C, Jin S J*. Free tool central point total focusing method for imaging large-size curved components under robotic automation ultrasonic testing[J]. Measurement. 2025, 256: 118493.

[12] Fan S G, Zhang P, Meng Y Y, Liu H H, Luo Z B*, Jin S J*. Ratcheting damage evaluation based on critically refracted longitudinal wave combined with recurrence quantification analysis[J]. Measurement. 2025, 242: 115970.

[13] Luo Z B*, Li F Z, Wang H, Zhang X Y, Li Y P, Jin S J*. Ultrasonic evaluation of early-stage hygrothermal aging damage for anisotropic composites based on PA-LCR technology[J]. NDT & E International. 2025, 156: 103470.

[14] Jin S J, Wang Z C, et al. TOFD detection of shallow subsurface defects in aluminum alloy thin plates by half-skip mode-converted wave[J]. Chinese Journal of Aeronautics. 2024, 37(6): 454-463.

[15] Jin S J, Di C J, et al. Profile reconstruction of irregular planar defects by mirrored composite-mode total focusing method[J]. NDT & E International. 2024, 141: 102979.

[16] Jin S J, Wang X H, et al. Defect detection of spherical heads by time-of-flight diffraction[J]. Applied Acoustics. 2024, 216: 109787.

[17] Jin S J, Sun X, et al. Reducing dead zone in ultrasonic time-of-flight diffraction (TOFD): a review[J]. Russian Journal of Nondestructive Testing. 2024, 60(2): 170-187.

[18] Luo Z B*, Liu Z H, Li F Z, Jin S J*. Defects imaging in corner part with surface adaptive ultrasonic testing and focusing in receiving (FiR) strategy[J]. Journal of Nondestructive Evaluation. 2024, 43: 49.

[19] 李潇，罗忠兵，孙浩，冯伟伦，金士杰*. 基于Var-MRLA稀疏方法的自适应全聚焦成像[J]. 机械工程学报. 2026, 62(10): 41-49.

[20] Feng W L, Li X, Sun H, Luo Z B, Jin S J*. Artifact suppression in ultrasonic TFM imaging of curved surface components by zero-phase filtering[C]. Far East NDT New Technology & Application Forum 2025. Wuhan, China: 2025.