四川宜宾人，中共党员，获批主持基金委首批国自然博士生项目。研究方向为装备健康监测与诊断（信号处理+机器学习）等，创新成果包括准算数均值比框架、新型稀疏测度、脉冲模态分解、优化权重谱、差异模态分解等，在MSSP，IEEE/ASME Transactions等权威期刊发表一作SCI论文10余篇（含11篇中科院1区Top），其中3篇入选ESI高被引；谷歌学术总被引800余次，H-index=17；在Elsevier出版英文学术专著一部。获ICSMD 2022国际会议论文Best paper奖（一作）、上海交大研究生学术之星提名奖、博士生国家奖学金（2次）、IEEE TIM杰出审稿人奖（3次）等荣誉或奖励。

五篇代表作：

1. Hou B, Wang D*, Xia T, Wang Y, Zhao Y, Tsui K. Investigations on quasi-arithmetic means for machine condition monitoring[J]. Mechanical Systems and Signal Processing, 2021, 151: 107451.

2. Hou B, Xie M, Yan H, Wang D*. Impulsive mode decomposition[J]. Mechanical Systems and Signal Processing, 2024, 211:111227.

3. Hou B, Wang D*, Kong J, Liu J, Peng Z, Tsui K-L. Understanding importance of positive and negative signs of optimized weights used in the sum of weighted normalized Fourier spectrum/envelope spectrum for machine condition monitoring[J]. Mechanical Systems and Signal Processing, 2022, 174: 109094.

4. Hou B, Wang D*, Yan T, Wang Y, Peng Z, Tsui K-L. Gini Indices II and III: Two new sparsity measures and their applications to machine condition monitoring[J]. IEEE/ASME Transactions on Mechatronics, 2022, 27(3): 1211–1222.

5. Hou B, Wang D*, Peng Z, Tsui K-L. Adaptive fault components extraction by using an optimized weights spectrum based index for machinery fault diagnosis[J]. IEEE Transactions on Industrial Electronics, 2023: 1–10.  

谷歌学术：

https://scholar.google.com/citations?user=O_tweiYAAAAJ&hl=en&oi=sra

ResearchGate：

https://www.researchgate.net/profile/Bingchang-Hou-2

非常欢迎同学加入本课题组,将结合自身成长经验认真指导学生，最大限度帮助同学成长成才，Email:binghcnaghou@cqu.edu.cn。