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-informed deep learning.

Publications

  • Bridging Physics-based and Data-driven modeling for Learning Dynamical Systems
  • Rui Wang, Danielle Maddix, Christos Faloutsos, Yuyang Wang, Rose Yu.
    Under review
  • Incorporating Symmetry into Deep Dynamics Models for Improved Generalization
  • Rui Wang*, Robin Walters*, Rose Yu. (*equal contribution)
    Under review
  • 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.
    Contributed Talk 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
    • ODEs-informed time series forecasting.

    Machine Learning Research Intern

    2019.05 - 2019.08
    Lawrence Berkeley National Laboratory, Berkeley, CA
    • Towards Physics-informed Deep Learning for Turbulent Flow Prediction.

    Research Assistant

    2019.01 - 2019.04
    Northeastern University, Boston, MA
    • Aortic Pressure Forecasting with Deep Sequence Learning

    Graduate Teaching Assistant

    2019.01 - 2019.04
    Northeastern University, Boston, MA
    • Special Topics in Artificial Intelligence.

    Data Science Co-op

    2018.07 - 2018.12
    Abiomed Inc., Danvers, MA
    • Healthy Heart Index, patients’ survival probabilities prediction.

    Research Assistant

    2018.04 - 2018.11
    Northeastern University, Boston, MA
    • TRACE (Teacher Rating and Course Evaluation) data evaluation with Bayesian Binomial Regression.

    Awards/Honors

    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