Dr. ZHANG joined Zhejiang Lab in March 2021 and is currently a principal investigator at the Research Center for Humanoid Sensing and Perception. He earned his bachelor’s and master’s degrees in Automotive Engineering from Tongji University in 2007-2014. Then, he earned his doctoral degree from the Institute of Sound and Vibration Research (ISVR) at the University of Southampton, UK, in 2014-2019, supervised by Professor David Thompson. His postdoctoral research was also conducted in ISVR, supervised by Professor Stephen Elliot, a Fellow of the Royal Academy of Engineering. Dr. ZHANG’s research focuses on algorithm development for multichannel audible sound processing systems, including analysis of rail transit noise, sensor array design and algorithm development, research on adaptive active noise control algorithm, etc. 

Apr 2019-Dec 2020, participated in the DigiTwin Project funded by the Engineering and Physical Sciences Research Council, UK, and was responsible for research into control algorithms, one of its subprojects. 

Journal Publications:

1. J. Zhang, G. Squicciarini, D. J. Thompson. (2019). Implications of the directivity of railway noise sources for their quantification using conventional beamforming. Journal of Sound and Vibration, 459, 114841.

2. Zhang, J., Elliott, S. J., & Cheer, J. (2021). Robust performance of virtual sensing methods for active noise control. Mechanical Systems and Signal Processing, 152, 107453.

3. Elliott, S. J., Zhang, J., Kwan Lai, C., & Cheer, J. (2020). Superposition of the uncertainties in acoustic responses and the robust design of active control systems. The Journal of the Acoustical Society of America, 148(3), 1415-1424. (communication author).

4. Liu, X., Zhang, J., Thompson, D., Iglesias, E. L., Squicciarini, G., Hu, Z., ... & Lurcock, D. (2021). Aerodynamic noise of high-speed train pantographs: Comparisons between field measurements and an updated component-based prediction model. Applied Acoustics, 175, 107791.

5. Thompson, D., Squicciarini, G., J. Zhang, Arteaga, I. L., etc. (2018). Assessment of measurement-based methods for separating wheel and track contributions to railway rolling noise. Applied Acoustics, 140, 48-62.

6. J. Zhang, D. J. Thompson, G. Squicciarini, et al. A hybrid beamforming method for high-speed moving sources, Mechanical Systems and Signal Processing (Under Review).