Biography

I received Ph.D degree in seismology at Nanjing University. My research focuses on advancing seismic tomographic techniques for investigating earth’s internal structure. I specializes in using receiver function, surface wave and local earthquakes to image earth discontinuities, velocity structures and anisotropies.

Since Dec 2021, I have joined Mathematical Imaging and Geophysics Group at Nanyang Technological University as a research fellow.

I am an advocate of open source as core developer of the Seispy in receiver functions processing and FWAT in full-waveform inversion.

Interests
  • Seismic Imaging and Tomography
  • Adjoint-state Full-waveform Inversion
  • Wavefield Simulation in Complex Media
  • Continental Geodynamics
Education
  • Ph.D in Geology, 2021

    Nanjing University

  • MSc in Geophysics, 2016

    Nanjing University

Experience

 
 
 
 
 
Research Fellow
Dec 2021 – Present Singapore
 
 
 
 
 
Software Engineer
Jun 2017 – Jun 2018 Nanjing

Responsibilities include:

  • CRV test for digital unit in Base Station.
  • Automation developing for CRV test.
  • Continuous integration for iterations of operating system in digital unit.
 
 
 
 
 
Research Assistant
Jul 2016 – May 2017 Nanjing
Taught experimental part of “Introduction to Seismology”.

Projects

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Full-waveform inversion joint with multiple data types
Different data types have different sensitivities to different anomalies. For example, ambient noise surface wave data has good lateral resolution in shallow depth, while teleseismic waveform and receiver function data have good vertical resolution. By combining multiple data types within the framework of full-waveform inversion (adjoint tomography) and jointly optimizing the velocity model, we can obtain a more reliable and accurate velocity structure.
Receiver Function Adjoint Tomography
Receiver function (RF) is widely used for imaging crustal and uppermost mantle velocity structure based on horizontal layered assumption. However this traditional technique has limitations on resolving non-layered anomalies, such as the dipping Moho, the subduction zone, and plumes. Thus, we develop a innovative technique to invert RFs based on adjoint waveform tomography method for high-resolution seismic array imaging.
Seispy: Python Module for Batch Calculation and Postprocessing of Receiver Functions
Seispy is a graphical interface Python module for receiver function (RF) calculation and post-processing in seismological research. Automated workflows of RF calculations facilitate processing large volumes of different types of seismic data.
Crustal Structures in the SE Tibet
Moho depth and crustal deformation in the SE Tibet
Mantle Transition Zone Structure in SE Tibet
Using Receiver Function method to estimate the topography of MTZ under SE Tibet

Software

Source Codes

Python

Seispy: Python module of seismology and receiver functions
CCCN: Cross-Correlation for Coda and Noise
BQMail: Python scripts to request seismic data from IRIS DMC

Matlab

SplitRFLab: A Matlab toolbox of processing receiver functions and shear wave spliting

C/C++

STALTA: Detecting microearthquakes using STA/LTA method

Contact