Physics-Informed Neural Networks for PDEs
May 2021 – May 2022 · NWPU Innovation-and-Entrepreneurship Program (大创). Applied physics-informed neural networks to fit parameters of fundamental second-order PDEs — parabolic, elliptic, and hyperbolic — under initial- and boundary-condition constraints. Concluded with an Excellent Academic Paper rating.
Jiaxuan Liu
M.Eng. Student in Information & Communication Engineering · Speech AI Researcher
My research focuses on text-to-speech, expressive & emotional speech synthesis, multimodal movie dubbing, and speech foundation models.