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Postdoctoral Fellow
Research group |?Centre for Studies of the Physics of the Earth (NJORD)
Main supervisor |?Francois Renard
Co-supervisor |?-
Affiliation |?Department of Geosciences, UiO
Contact |?shutingm@uio.no
Short bio
I have a background in rock mechanics and geoscience, with a strong focus on experimental laboratory research. I completed my PhD in 2022 at the University of the Chinese Academy of Sciences, where my research investigated the effects of temperature, stress perturbations, and structural discontinuities on the mechanical behavior and fracture mechanisms of rocks. From March 2023 to August 2025, I worked as a Humboldt Research Fellow at the GFZ German Research Centre for Geosciences. My research at GFZ focused on hydraulic fracturing and shear processes in crystalline rocks relevant to geothermal energy applications, as well as on the characterization of deformation localization using distributed optical fiber sensing. In October 2025, I joined the Njord Centre as a postdoctoral researcher within the DSTrain project.
Research interests and hobbies
My research focuses on rock mechanics and geophysics, with a particular emphasis on applying advanced sensing and imaging technologies to quantify rock deformation, damage evolution, and fluid flow in geological materials. The goal of my research is to enhance understanding of and improve the prediction of subsurface processes relevant to CO? sequestration, hydrogen storage, geothermal energy exploitation, and hazardous fluid disposal, where the coupling between rock deformation and fluid transport is critical.
I have experience in characterizing deformation localization and fracture evolution using distributed optical fiber sensing, acoustic emission monitoring, and digital image correlation. Motivated by recent advances in high-resolution imaging, sensing, and large-scale experimental data, I am extending my research by integrating experimental geomechanics with artificial intelligence to uncover the underlying physical mechanisms in complex datasets and to improve predictions of geological hazards.
In my spare time, I enjoy swimming to keep fit and clear my head, hiking to explore nature and recharge my batteries, and cooking as a creative way to relax outside of work.
DSTrain project
Physics-informed U-net for Fluid Flow Prediction in Deformed Porous Rocks (SmartFlow)
Within the DSTrain project, I will first develop a core-scale dataset by combining synchrotron X-ray microtomography of deformed porous rock cores with computational fluid dynamics simulations to generate high-resolution pressure and velocity labels. Building on this dataset, I will develop a physics-informed U-Net that incorporates governing fluid dynamics equations to ensure physical consistency and robust generalization. The resulting AI model is expected to predict pressure and velocity fields across complex porous media several orders of magnitude faster than conventional simulations, providing a foundation for future upscaling to reservoir-scale applications and supporting sustainable subsurface resource management, including carbon sequestration and underground energy storage.
Image: AI-based fluid flow prediction in porous sedimentary rocks. The project SmartFlow targets the left side of the graph (pore to core scale), with potential upscaling to the reservoir scale.
Publications
DSTrain publications
Previous publications
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