Yanjie Song
- Email: cnys@leeds.ac.uk
- Thesis title: Physics-informed machine learning methods in solving multi-physics coupled equations
- Supervisors: Dr Xiaohui Chen, Professor He Wang
Profile
Mr Yanjie Song, PhD Candidate at the University of Leeds (UoL).
He focuses mainly on solving multi-physics coupled equations with Artificial Intelligence methods. Specifically, he is dedicated to the development of attention-based deep learning model under physics-informed frameworks and finding surrogate AI architectures in solving complex coupled problems. His loss-attentional based approaches have attracted widespread interest from the academic and industrial communities.
He also serves as the Editor Assistant for Geomechanics and Geoengineering.
Research interests
- Physics-Informed Machine Learning.
- Surrogate Solution Methods for Multi-Physics Coupling Equations.
- Transformer-based Deep Learning Models.
- Generative Adversarial Networks, GANs.
- Graph Neural Networks, GNN.
- Reinforcement Learning Model.
- Operator Learning.
Qualifications
- PhD Candidate, University of Leeds
- M.Eng., Shandong University
- B.Eng., Sichuan University