BIOGRAPHY
I am an Applied Scientist at Amazon. Before joining Amazon, I worked as an AI Scientist at GE Healthcare. I completed my postdoc at MIT under the guidance of Prof. Tess Smidt and obtained my Ph.D. in Computer Science from UC San Diego, where I was advised by Prof. Rose Yu. During my Ph.D. studies, I also had the opportunity to work as a research intern at Google Cloud AI, AWS, Berkeley Lab, and Lawrence Livermore National Lab.
My research spans AI for science, geometric deep learning, and spatiotemporal forecasting, with a focus on integrating prior scientific knowledge into deep learning models to enhance their accuracy, interpretability, and generalization ability for large-scale complex tasks.
Selected Publications
Advances in Neural Information Processing Systems (NeurIPS) 2024
International Conference on Machine Learning (ICML) 2024
Proceedings of the National Academy of Sciences (PNAS) 2024
International Conference on Learning Representations (ICLR) 2023
Advances in Neural Information Processing Systems (NeurIPS) 2022
International Conference on Machine Learning (ICML) 2022
International Conference on Learning Representations (ICLR) 2021
Annual Conference on Learning for Dynamics and Control (L4DC) 2021
ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) 2020