Tiange Xiang

Tiange Xiang is a Ph.D. student at Stanford University, affiliated with the Stanford AI Lab and Stanford Vision and Learning Lab. His research bridges generative models and AI for healthcare, focusing on 3D human reconstruction, medical imaging, and diffusion model applications.

• Education: Ph.D. and M.S. in Computer Science at Stanford University; B.S. in Computer Science and Technology (Advanced) at the University of Sydney.
• Advisors: Prof. Fei-Fei Li, Prof. Scott Delp, and Prof. Ehsan Adeli.

His work includes foundational contributions to occluded human rendering (OccFusion, Wild2Avatar), medical anomaly detection (Exploiting Structural Consistency of Chest Anatomy, SQUID), and fMRI vision decoding (Seeing Beyond the Brain). He has pioneered 3D Gaussian splatting and score-distillation sampling techniques. Collaborators include leading researchers from Google DeepMind and Stanford.

• Scientific Awards: University Medal (University of Sydney), Stanford HAI Fellowship, Qualcomm Innovation Fellowship Finalist.

He has served as a conference reviewer for CVPR, MICCAI, ICCV, and others, and as a teaching assistant for courses like CS 231n. His code repositories for BiO-Net and OccFusion are widely shared and implemented in Python.