Xianghao Zhan

Traumatic brain injury (TBI) has become a global public health challenge. If undetected, the brain damage from TBI can accumulate, calling for better TBI modeling and warning systems. TBI modeling involves three stages: measurement of head impact kinematics, brain deformation, and injuries. In this project, I will leverage machine learning and head impact data to optimize the TBI computational modeling: the measurement precision of head kinematics will be improved and the fast, accurate, and generalizable brain deformation modeling will be done with deep learning. Furthermore, I will leverage animal experiments to investigate the link between brain deformation and the TBI pathologies for injury-predictive models.