BIOGRAPHY

I am an AI Research Scientist at GE Healthcare. Before that, I was fortunate to work as a Postdoc at MIT, under the guidance of Prof. Tess Smidt. I completed my Ph.D. in Computer Science at UC San Diego, where I had the privilege of being advised by Prof. Rose Yu. Throughout my Ph.D. studies, I 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 healthcare, AI for science, geometric deep learning, and spatiotemporal modeling, with a focus on integrating scientific knowledge into deep learning models to enhance their accuracy, interpretability, and generalization for large-scale complex tasks.

Selected Publications

  • Segment as You Wish - Free-Form Language-Based Segmentation for Medical Images.
  • Longchao Da*, Rui Wang*, Xiaojian Xu, Parminder Bhatia, Taha Kass-Hout, Hua Wei, Cao Xiao.
    Preprint
  • A Recipe for Charge Density Prediction
  • Xiang Fu, Andrew Rosen, Kyle Bystrom, Rui Wang, Albert Musaelian, Boris Kozinsky, Tess Smidt, Tommi Jaakkola.
    Advances in Neural Information Processing Systems (NeurIPS) 2024
  • Discovering Symmetry Breaking in Physical Systems with Relaxed Group Convolution
  • Rui Wang, Elyssa Hofgard, Han Gao, Robin Walters, Tess E.Smidt.
    International Conference on Machine Learning (ICML) 2024
  • Learning Dynamical Systems from Data - An Introduction to Physics-Guided Deep Learning
  • Rose Yu, Rui Wang.
    Proceedings of the National Academy of Sciences (PNAS) 2024
  • Koopman Neural Forecaster for Time Series with Temporal Distribution Shifts
  • Rui Wang, Yihe Dong, Sercan O Arik, Rose Yu.
    International Conference on Learning Representations (ICLR) 2023
  • Meta-Learning Dynamics Forecasting Using Task Inference
  • Rui Wang*, Robin Walters*, Rose Yu.
    Advances in Neural Information Processing Systems (NeurIPS) 2022
  • Approximately Equivariant Networks for Imperfectly Symmetric Dynamics
  • Rui Wang*, Robin Walters*, Rose Yu.
    International Conference on Machine Learning (ICML) 2022
  • Incorporating Symmetry into Deep Dynamics Models for Improved Generalization
  • Rui Wang*, Robin Walters*, Rose Yu.
    International Conference on Learning Representations (ICLR) 2021
  • Bridging Physics-based and Data-driven Modeling for Learning Dynamical Systems
  • Rui Wang, Danielle Maddix, Christos Faloutsos, Yuyang Wang, Rose Yu.
    Annual Conference on Learning for Dynamics and Control (L4DC) 2021
  • Towards Physics-informed Deep Learning for Turbulent Flow Prediction
  • Rui Wang, Karthik Kashinath, Mustafa Mustafa, Adrian Albert, Rose Yu.
    ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) 2020