Dr.Kunning Tang is a postdoctoral researcher in minerals and energy engineering whose research focuses on digital rock analysis, applied artificial intelligence, and in-situ recovery (ISR) of critical minerals. His work integrates multi-scale imaging, data-driven methods, and physics-based modelling to quantitatively characterise porous and mineralised materials and to unravel coupled transport–reaction processes in complex geological systems. He develops advanced AI frameworks for multi-scale image enhancement, segmentation, and domain transfer, enabling high-fidelity digital twins across various scales. A central theme of his research is the pore-scale mechanistic understanding of electrokinetic ISR, where he investigates multiphase flow, ion transport, and mineral dissolution–precipitation reactions under coupled hydraulic and electric fields using time-lapse micro-CT experiments and reactive transport modelling. His expertise further extends to mineral characterisation, combining micro-CT, micro-XRF, and XRD with grain-scale analysis to bridge pore-scale mechanisms and core-scale behaviour, supporting the development of predictive and sustainable mineral recovery