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Ray Wang (王睿)

Machine Learning PhD student

Education

Ph.D. student in CompSci

UC San Diego
2020 - Present

Ph.D. student in CompSci

Northeastern University (transferred to UCSD)
2019 - 2020

M.S in Data Science

Northeastern University
2017 - 2019

Exchange Student

UC Berkeley
2016

B.S in Applied Mathematics

Huazhong Uni. of Sci. and Tech.
2013 - 2017

BIOGRAPHY

I am a 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. For more details, see my curriculum vitae.

Selected Publications

  • Physics-Guided Deep Learning for Dynamical Systems, A Survey
    • Rui Wang, Rose Yu.
    Under review
  • Meta-Learning Dynamics Forecasting Using Task Inference
    • Rui Wang*, Robin Walters*, Rose Yu.
    Under review
  • Latent Space Simulation for Carbon Capture Design Optimization.
    • Brian Bartoldson, Rui Wang, Yucheng Fu, David Widemann, Sam Nguyen, Jie Bao, Zhijie Xu, Brenda Ng.
    Annual Conference on Innovative Applications of Artificial Intelligence (IAAI) 2022
  • Incorporating Symmetry into Deep Dynamics Models for Improved Generalization
    • Rui Wang*, Robin Walters*, Rose Yu. (*equal contribution)
    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
  • 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
  • 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
    • Rui Wang*, Eliza Huang*, Uma Chandrasekaran, Rose Yu. (*equal contribution)
    Computing in Cardiology 2020

    Experiences

    Research Intern

    2021.06 - 2021.09
    Lawrence Livermore National Laboratory, Livermore, CA

    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