Jing Hu Associate professor

• Department: Department of Geophysics
• Gender: male
• BirthDate: 1992-06-02
• Career: Associate professor
• Degree: PhD
• Academic Credentials: University of Science and Technology of China
• Graduate School:
• Tel:
• Email: hujing@chd.edu.cn
• Address School:
• PostCode School: 710054
• Fax School:
• Office Location: Room 211, Second Teaching Building, Yanta Campus
• Education experience:

  • Ph.D. in Solid Earth Geophysics
    University of Science and Technology of China (USTC), 2020
    Supervised by Prof. Haijiang Zhang

  • Visiting Scholar
    University of Southern California (USC), 2018–2019
    Supervised by Prof. Yehuda Ben-Zion

  • B.E. in Exploration Technology and Engineering
    Chang'an University, 2014

  
  

Jing Hu is an Associate Professor and Master's Supervisor at Chang'an University. He received his Bachelor of Engineering degree in Exploration Technology and Engineering from Chang'an University (2010–2014) and his Doctor of Science degree in Solid Earth Geophysics from the University of Science and Technology of China (USTC) (2014–2020). His research interests include seismic tomography (body-wave travel-time tomography, body-wave attenuation tomography, ambient noise tomography, time-lapse tomography), array signal processing, and applications of artificial intelligence in geophysics.

Graduate Student Recruitment

Students interested in Geophysics / Artificial Intelligence / Software Development are welcome to apply. Undergraduate students are also encouraged to consult regarding academic directions and related matters.

Contact: Email: hujing@chd.edu.cn or Phone: 187-0098-9336

Requirements for Graduate Students

• Integrity and team spirit

• Passion and motivation for scientific research

• Strong learning ability and independent thinking skills

• Basic scientific research literacy and fundamental skills in scientific computing

1) Seismic travel-time tomography, three-dimensional body-wave Q-value tomography, and velocity change imaging

2) Array signal processing & rapid detection of weak signals

3) Exploration of deep learning applications in seismic inversion

5) 2025 – Anhui Provincial Postdoctoral Science Foundation (Grade C): Joint Inversion of 3D Q-Value, 30,000 RMB, Grant No. 2015C1142, Principal Investigator

4) 2024 – National Major Deep Earth Science and Technology Project: XXX Transparent Geological Model (Topic), 500,000 RMB, Principal Investigator

3) 2022.01–2024.12 – National Natural Science Foundation of China (NSFC) Young Scientist Fund: XXX Deep Learning Joint Inversion, 300,000 RMB, Principal Investigator

2) 2022.02–2023.12 – Fundamental Research Funds for the Central Universities: XX Attenuation Imaging, 80,000 RMB, Principal Investigator

1) 2022.01–2024.12 – National Natural Science Foundation of China (NSFC) General Program: 590,000 RMB, Participant

Selected Publications (as Corresponding or First Author)

1. Dong, Q., Qiu, H., Hu, J.*, et al. (2026). A deep learning-based forward surrogate model for accelerating surface-wave dispersion inversion. Seismological Research Letters. https://doi.org/10.1785/0220260035

2. Wang, Y., Hu, J.*, Ma, Y., et al. (2026). Study of the seismogenic mechanism and three-dimensional velocity structure of the source region of the MS6.8 earthquake in Dingri, Xizang on January 7, 2025. Chinese Journal of Geophysics, 69(3), 1046–1064. (in Chinese)

3. Hao, A., Hu, J.*, Ji, X., et al. (2026). Research on construction method of 3D geomagnetic reference map based on U-Net neural network. Journal of Air Force Engineering University, 27(2), 42–53. (in Chinese)

4. Hu, J., Wang, S., Shang, C., Xiao, Y., & Shao, G. (2025). Design and implementation of surface wave dispersion imaging platform based on PyQt5. Acta Seismologica Sinica, 47(3), 410–421. (in Chinese)

5. Hu, J., Zhao, T., Bai, C., Guo, H., Wang, Y., Li, X., & Xin, H. (2021). 3D P and S wave velocity structures and earthquake relocation in the source area of the 21 May 2021 Yangbi Ms6.4 earthquake. Chinese Journal of Geophysics, 64(12), 4488–4509. (in Chinese)

6. Hu, J., Qiu, H., Zhang, H., & Ben-Zion, Y. (2020). Using deep learning to derive shear wave velocity models from surface wave dispersion data. Seismological Research Letters, 91(3), 1738–1751.

7. Hu, J., Zhang, H., & Yu, H. (2018). Accurate determination of P-wave backazimuth and slowness parameters by sparsity-constrained seismic array analysis. Geophysical Journal International, 216(1), 1–18.

2024.12 – Present, Chang'an University, Associate Professor

2021.01 – 2024.12, Chang'an University, Lecturer