Jianing Gou is a PhD candidate from Chinese academy of sciences who focuses on machine learning and digital signal processing in geophysics and geodesy now. His research is directed toward understanding the structure of the Earth’s deep interior, Geodynamics, and interpretation of Geodetic data anomaly during seismic or other geophysics events.

He has strong knowledge of C/C++, Python, Java, shell and matlab programming. With these skills, he created quite a few widely used applications and packages in geodesy and geophysics.

He is also a big fan of open-source who interested in algorithms design and computer science technology applied in geoscience.

Download my full CV here.

Interests
  • Time series analysis
  • Digital signal processing
  • Parallel computing
  • Algorithm design and software development in geodesy and geophysics
  • Deep Learning
Education

  • Master. in Geophysics, 2022

    Institute of Seismology, CEA. Wuhan, China

  • P10 Program. Communication Technology and Application, 2020

    Chinese Academy of Sciences. Beijing, China

  • BSc in Applied Geophysics and English(Second Major), 2019

    Chengdu University of Technology. Chengdu, China

Research

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All Deep Learning Gravity noise level
Last updated on May 2, 2022
Classification of Background Noise and Gravity Disturbance Signals
Classification of Background Noise and Gravity Disturbance Signals

Summary: In order to cope with the huge challenge of artificial-based processing and analysis brought by the surge of continuous gravity data, this paper attempts to use deep scattering network to extract features from gravity data, and use unsupervised Gaussian mixture model to classify earthquake-related signals and background noise.
Last updated on May 2, 2022
Gravimeter background noise level
Gravimeter background noise level

Summary: the research on the background noise of the gravimeter is helpful for the site selection of the station, the adjustment of the instrument, the judgment of whether the instrument has the ability to detect the normal mode of earthquake in the near future, and the detection of weak geodynamic signals.

Featured Publications

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April, 2022 Reviews of Geophysiscs and Planetary Physics noise level
Analysis of background noise level of PET/gPhone gravimeter in Mainland China

In order to evaluate the background noise level of PET/gPhone gravimeter of the National Gravity Network, we collected and processed 4a continuous gravity data recorded by the 52 PET/gPhone gravimeters from 2014 to 2017.

(1) DaySNM method can find the lowest SNM, compared with the Banka and Bandpass method.

(2) the variation range of SNM (Seismic Noise Level) in mainland China is 2.013 (Yutian) ~ 4.654 (Yinchuan), and the variation range of SSNM (SubSeismic Noise Level) is 5.024 (Gelmud) ~ 6.500 (Liyang).

(3) SNM in coastal areas generally larger than inland gravimeters. Conclusions: Our study suggested that wave pulsation may be the main reason for the loud noise of coastal stations; eastern and northern Qinghai-Tibet Plateau, which may be related to frequent geological tectonic activities in these areas;
DOI

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