Shunyu Wu (吴舜禹)

About

I study the dynamics of physical systems and develop learning methods for their control and optimization. My work connects models of evolving physical states with decisions about system operation and manufacturing conditions. I am particularly interested in neural operators for distributed dynamics and in how model errors affect the resulting decisions.

My engineering interests lie in water-energy systems, with a current emphasis on the dynamics and sustainable operation of integrated multi-energy systems serving data centers. I am interested in how computing demand interacts with cooling and energy supply, and how these interactions affect energy and water use alongside carbon emissions.

My scientific work focuses on dynamic modeling and optimization for precision materials manufacturing. I work with Professor Fengqi You to model how material structure evolves during processing and to optimize processing conditions for desired structures.

I am an Ezra Systems Postdoctoral Associate in Systems Engineering at Cornell University. I completed my Ph.D. at Shanghai Jiao Tong University in 2026, advised by Professor Jingcheng Wang.

Research

learnoptimizedecision error trains the modelAPhysical dynamicswater-energy and materialsBLearning dynamicspredict evolving physical fieldsCModel2Actioncontrol and optimizationact APhysical dynamicswater-energy and materialslearnoptimizeactBLearning dynamicspredict evolving physical fieldsCModel2Actioncontrol and optimizationdecision error trains the model APhysical dynamicswater-energy and materialsBLearning dynamicspredict evolving physical fieldsCModel2Actioncontrol and optimizationlearnoptimizedecision error trains the modelact

The full research program

News

  1. Joined Cornell University as an Ezra Systems Postdoctoral Associate! I work with Professor Fengqi You on dynamic modeling and optimization for precision materials manufacturing.
  2. Invited to review for ICLR 2027!
  3. DRIFT appeared in Expert Systems with Applications.
  4. Received my Ph.D. from Shanghai Jiao Tong University! I thank my advisor, Professor Jingcheng Wang, and my labmates for six good years.
  5. SPTO appeared in IEEE Transactions on Smart Grid.

All news

Selected publications

  1. Figure 2 from SPTO: probabilistic forecasting, water-energy scheduling, and surrogate-loss training

    End-to-End Stochastic Predict-Then-Optimize for Cost-Efficient Water-Energy Resource Scheduling

    Shunyu Wu, Jingcheng Wang, Haotian Xu, Yanjiu Zhong, and Jun Rao

    IEEE Transactions on Smart Grid, 2025 First author

  2. Figure 2 from KbBcM: lag-penalty attention, AR-LSTM, and posterior correction

    Knowledge-based Bi-correction model for achieving effective lag-free characteristic on daily urban water demand forecasting

    Shunyu Wu, Jingcheng Wang, Haotian Xu, Shangwei Zhao, and Jiahui Xu

    Expert Systems with Applications, 2024 First author

  3. Figure 2 from CritiCoder: coupled Coder and Critic networks with two training loops

    CritiCoder: An End-to-End Uncertain Regression Network for Robust Macroscopic Pressure Models in Water Distribution Systems

    Shunyu Wu, Jingcheng Wang, Haotian Xu, Shangwei Zhao, and Jiahui Xu

    IEEE Transactions on Computational Social Systems, 2024 First author

  4. Figure 2 from DRIFT: local LiDAR point clouds and sparse graph nodes with a magnified scene detail

    DRIFT: Coordinating target intent and local geometry for diffusion-based trajectory generation

    Jinyang Zhao, Handong Zheng, Yanjiu Zhong, Qiang Zhang, and Shunyu Wu

    Expert Systems with Applications, 2026 Last author

  5. Figure 1 from the constrained RL controller paper: NMPC initialization and actor-critic feedback

    Reinforcement Learning Controller Design for Discrete-Time-Constrained Nonlinear Systems With Weight Initialization Method

    Jiahui Xu, Jingcheng Wang, Yanjiu Zhong, Jun Rao, and Shunyu Wu

    IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2024 Last author

All publications by year

Academic service

I reviewed for ICLR in the 2025 and 2026 cycles and have been invited for 2027. I have also reviewed for ICML, NeurIPS, AAAI, and CDC, and for five IEEE Transactions journals, Scientific Reports, and Socio-Economic Planning Sciences.

Reviewing, teaching, and mentoring

Citation geography

Institutions

Thinking

What status buys

We chase money and status largely for the life they can buy. If AI expands supply and makes that life affordable to more people, climbing the hierarchy becomes less necessary and following an interest becomes easier. If the bubble bursts without delivering those gains, why panic about missing a revolution that never arrived?

All notes