Xiaoyang is a Ph.D. student in Petroleum Engineering at Texas A&M University focused on subsurface lithology characterization and data-driven formation evaluation. His research integrates quantitative XRD and XRF characterization of drill cuttings with mud-logging, drilling, and well-log data to investigate relationships among mineral composition, geochemistry, formation properties, and drilling response. These efforts aim to establish a multimodal subsurface characterization database and develop physics-constrained machine-learning methods for rapid lithology classification and mineral-composition estimation. Before joining Texas A&M, his research focused on hydraulic fracturing, including treatment-pressure prediction, screenout-risk assessment based on net-pressure response characteristics, and pumping-schedule optimization.