BIOGRAPHY

I am a second-year PhD student at UC San Diego department of Computer Science and Engineering advised by Prof. Rose Yu, previously at Northeastern University. I received my Bachelor degree of science in Applied Mathematics from Huazhong University of Science and Technology. My research interests are in spatiotemporal learning and physics-guided deep learning. Here is my resume.

Publications

  • Meta-Learning Dynamics Forecasting Using Task Inference
  • Rui Wang, Robin Walters, Rose Yu.
    Under review
  • 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
  • Incorporating Symmetry into Deep Dynamics Models for Improved Generalization
  • Rui Wang*, Robin Walters*, Rose Yu. (*equal contribution)
    International Conference on Learning Representations (ICLR) 2021
  • Physics-informed Machine Learning, Case Studies for Weather and Climate Modelling
  • K. Kashinath, M. Mustafa, A. Albert, JL. Wu, C. Jiang, S. Esmaeilzadeh ,K. Azizzadenesheli, R. Wang, A.Singh, A. Manepalli, D. Chirila, R.Yu, R. Walters, B. White, H. Xiao, H. A. Tchelepi, P. Marcus, A. Anandkumar, Prabhat.
    Journal of Philosophical Transactions of the Royal Society A, 2020
  • Learning Dynamical Systems Requires Rethinking Generalization
  • Rui Wang, Danielle Maddix, Christos Faloutsos, Yuyang Wang, Rose Yu.
    NeurIPS, Interpretable Inductive Bias and Physically Structured Learning Workshop, 2020
  • Physics-based vs. Data-driven A Benchmark Study on COVID-19 Forecasting.
  • Rui Wang, Danielle Maddix, Christos Faloutsos, Yuyang Wang, Rose Yu.
    Best Paper Award at NeurIPS, Machine Learning in Public Health Workshop, 2020
  • 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
  • Aortic Pressure Forecasting with Deep Sequence Learning
  • Eliza Huang*, Rui Wang*, Uma Chandrasekaran, Rose Yu. (*equal contribution)
    Computing in Cardiology 2020
  • Towards Physics-informed Deep Learning for Turbulent Flow Prediction
  • Rui Wang, Adrian Albert, Karthik Kashinath, Mustafa Mustafa, Rose Yu.
    Contributed Talk at NeurIPS, Machine Learning for Physical Sciences Workshop, 2019
  • Prediction of Alzheimer's Disease-associated Genes by Integration of GWAS Summary Data and Expression data
  • Sicheng Hao, Rui Wang, Yu Zhang, Hui Zhan.
    Frontiers in Genetics 2018

    Experiences

    Applied Scientist Intern

    2020.05 - 2020.08
    Amazon Web Services, Palo Alto, CA

    Machine Learning Research Intern

    2019.05 - 2019.08
    Lawrence Berkeley National Laboratory, Berkeley, CA

    Research Assistant

    2019.01 - 2019.04
    Northeastern University, Boston, MA

    Graduate Teaching Assistant

    2019.01 - 2019.04
    Northeastern University, Boston, MA

    Data Science Co-op

    2018.07 - 2018.12
    Abiomed Inc., Danvers, MA

    Research Assistant

    2018.04 - 2018.11
    Northeastern University, Boston, MA

    Awards/Honors

    Best Paper Award - NeurIPS, Machine Learning in Public Health Workshop (2020)
    Student Registration Award - KDD (2020)
    Graduate Fellowship - Northeastern University (2019)
    Best Co-op Prize - Abiomed Inc. (2018)
    Outstanding Undergraduate - Huazhong University of Science and Technology (2017)
    Scholarship for Outstanding Learning - Huazhong University of Science and Technology (2014 - 2017)
    National Scholarship - Huazhong University of Science and Technology (2014)

    Skills & Proficiency

    Python & Pytorch & R

    Tensor Flow & Keras

    C & C++ & C# & SQL

    Matlab & JavaScript