Zhuoyuan Jacob Wang

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Hi, I’m a final year PhD in Electrical and Computer Engineering at Carnegie Mellon University, advised by Prof. Yorie Nakahira. Prior to joining CMU, I obtained my Bachelor degree at Tsinghua University, advised by Prof. Gao Huang and Prof. Yilin Mo.

My research interests include safety-critical control, physics-informed learning, stochastic systems and robotics.

Contact: zhuoyuaw [at] andrew.cmu.edu
Follow: Google Scholar | LinkedIn | jacobwang925

news

Aug 22, 2025 Our paper “Neural Spline Operators for Risk Quantification in Stochastic Systems” is accepted at CDC 2025!
Mar 21, 2025 I completed my Thesis Prospectus, titled “Bridging Physics and Learning: Safe and Efficient Control Systems with Theoretical Guarantees”!

selected publications

  1. CDC 2025
    Neural Spline Operators for Risk Quantification in Stochastic Systems
    Zhuoyuan Wang, Raffaele Romagnoli , Kamyar Azizzadenesheli , and Yorie Nakahira
    arXiv preprint arXiv:2508.20288, 2025
    arXiv Code
  2. AAAI 2024
    Physics-informed representation and learning: Control and risk quantification
    Zhuoyuan Wang, Reece Keller , Xiyu Deng , Kenta Hoshino , Takashi Tanaka , and Yorie Nakahira
    Proceedings of the AAAI Conference on Artificial Intelligence , 2024
    arXiv Code
  3. ICRA 2024
    Towards proactive safe human-robot collaborations via data-efficient conditional behavior prediction
    Ravi Pandya , Zhuoyuan Wang, Yorie Nakahira , and Changliu Liu
    2024 IEEE International Conference on Robotics and Automation (ICRA) , 2024
    arXiv
  4. L4DC 2023
    A Generalizable Physics-informed Learning Framework for Risk Probability Estimation
    Zhuoyuan Wang, and Yorie Nakahira
    Learning for Dynamics and Control Conference , 2023
    arXiv Code
  5. ACC 2022
    Myopically verifiable probabilistic certificate for long-term safety
    Zhuoyuan Wang, Haoming Jing , Christian Kurniawan , Albert Chern , and Yorie Nakahira
    2022 American Control Conference (ACC) , 2022
    arXiv Code
  6. L-CSS
    Scalable Long-Term Safety Certificate for Large-Scale Systems
    Kenta Hoshino , Zhuoyuan Wang, and Yorie Nakahira
    IEEE Control Systems Letters, 2023
  7. TPAMI
    Self-supervised discovering of interpretable features for reinforcement learning
    Wenjie Shi , Gao Huang , Shiji Song , Zhuoyuan Wang, Tingyu Lin , and Cheng Wu
    IEEE Transactions on Pattern Analysis and Machine Intelligence, 2020
    arXiv