Hello, I am a final-year PhD student advised by Prof. Shuiwang Ji. During my PhD, I focused on developing deep learning methods for scientific problems, including deep-learning-based physics simulation and computational chemistry.
Prior to my PhD, I received my master's degree in engineering from Shanghai Jiao Tong University, my engineer's degree from ENSTA Paris, and my bachelor's degree from Shanghai Jiao Tong University.
I am currently on the 2026 job market.
Publications
- Orbital Transformers for Predicting Wavefunctions in Time-Dependent Density Functional Theory International Conference on Learning Representations (ICLR 2026)
- A Two-Phase Deep Learning Framework for Adaptive Time-Stepping in High-Speed Flow Modeling International Conference on Learning Representations (ICLR 2026)
- A Geometry-Aware Message Passing Neural Network for Modeling Aerodynamics over Airfoils Best student solution prize @ NeurIPS 2024 - ML4CFD Competition
- SineNet: Learning Temporal Dynamics in Time-Dependent Partial Differential Equations International Conference on Learning Representations (ICLR 2024)
- Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems Foundations and Trends in Machine Learning | https://www.air4.science
- Group Equivariant Fourier Neural Operators for Partial Differential Equations International Conference on Machine Learning (ICML 2023)
- A Score-Based Model for Learning Neural Wavefunctions arXiv:2305.16540
- Lattice Convolutional Networks for Learning Ground states of Quantum Many-Body Systems SIAM International Conference on Data Mining (SDM 2023)
- Fast Quantum Property Prediction via Deeper 2D and 3D Graph Networks Tech Report, KDD Cup 2021, Runner-up award on OGB-LSC
- Quaternion Product Units for Deep Learning on 3D Rotation Groups IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2020)
Software
- Real time semantic slam in ROS with a hand held RGB-D camera Research intern at ENSTA Paris | URL: GitHub Repository