Yulai Zhang

Dr Yulai Zhang is a Distinguished Professor in the Department of PHY at The Australian National University. His research focuses on Micro-CT imaging of geomaterials, machine learning-based image processing, properties prediction of geomaterials from images and numerical simulation, and mineral processing. He works closely with industry collaborators from Anglo American Steelmaking Coal company, Rio Tinto, and Strata Control Technologies (SCT) on projects such as coal cleat mapping and ore material characterization for ore upgrading. His research involves the application of 3D X-ray microCT and image analysis for geomaterial characterization, including multimodal/multiscale imaging, new image analysis methods, and in situ dynamic experiments with CT. Recently, he has started exploring machine learning-based image processing methods for complex rock characterisation, using convolutional neural networks (CNNs) for segmentation in images with insufficient contrast and low quality.

Yulai Zhang is a Research Fellow at the Australian National University, specializing in X-ray microCT, image processing, machine learning, and ore characterization. Their research focuses on advanced imaging techniques to analyze geological materials, including coal and copper ores, with applications in mineral liberation, fracture mechanics, and diffusivity studies. Zhang's work integrates computational methods to enhance the accuracy of 3D quantification and characterization of complex geological structures. Publications highlight the use of dynamic micro-CT for time-lapsed visualization, pore-scale analysis, and multiscale characterization of shale and coal. Their research contributes to improving resource extraction and understanding subsurface processes.