I am an Assistant Professor at the School of Artificial Intelligence and Automation, Huaiyin Normal University (HYTC), which I joined in September 2026. Prior to this, I received my Ph.D. (2026) and M.S. (2022) in Computer Science and Technology from the National University of Defense Technology (NUDT) under the supervision of Prof. Jie Liu, Prof. Zeyao Mo, and Prof. Xinhai Chen, and my B.S. from Northwestern Polytechnical University (NWPU) in 2020.

My primary research interest lies in AI for Science (AI4S), with a particular focus on AI for Computational Fluid Dynamics (AI for CFD). Specifically, my work centers on intelligence-driven mesh generation, adaptive movement, and quality optimization, exploring how Graph Neural Networks (GNNs), Reinforcement Learning (RL), and unsupervised learning techniques can overcome fundamental bottlenecks in complex geometric physical simulations.

Openings & Industry/Academic Collaborations:

I am actively seeking self-motivated graduate and undergraduate students who are enthusiastic about AI4S, AI for CFD, and geometric deep learning; a solid background in mathematics and programming (e.g., PyTorch / C++) is preferred. Beyond academic research, I am keen to bridge the gap between AI algorithms and real-world engineering challenges. I warmly welcome collaborations with academic peers, industry partners, CAE software developers, and research institutes on topics such as intelligent mesh generation, simulation acceleration, and customized solver workflows. Feel free to reach out via email to discuss potential research collaborations or joint R&D projects.

🔥 Recent News

  • 2026.09 🏛️ Officially joined the School of Artificial Intelligence and Automation, Huaiyin Normal University (HYTC) as an Assistant Professor!
  • 2026.06 🎓 Successfully defended my Ph.D. dissertation and graduated from the National University of Defense Technology (NUDT)!
  • 2026.03 🎉 Our paper "A Fine-Grained Intelligent Mesh Quality Evaluation Algorithm Based on Neural Networks" was accepted by IJCNN 2026 (CCF-C).
  • 2026.01 🚀 Preprint "LLM4Fluid: Large Language Models as Generalizable Neural Solvers for Fluid Dynamics" is released on arXiv:2601.21681.
  • 2026.01 📄 Paper "Generalization-Aware Structured Mesh Smoothing via Graph Neural Networks" was accepted by Computers & Fluids.
  • 2025.10 💡 Our paper "GNNRL-Smoothing: A prior-free reinforcement learning model for mesh optimization" was published in Neural Networks (CAS Q2 Top, CCF-B, IF 6.3).
  • 2025.09 🔥 Our paper "UGM2N: An Unsupervised and Generalizable Mesh Movement Network via M-Uniform Loss" was accepted by NeurIPS 2025 (CCF-A)!
  • 2025.02 ✈️ Paper "A surface mesh smoothing method for aircraft based on unsupervised learning" published in Acta Aeronautica et Astronautica Sinica.
  • 2025.01 🏆 Awarded University-level Outstanding Student and Second-class Academic Scholarship at NUDT.

💡 Research Highlights

Intelligent Mesh Movement & Smoothing
Developing prior-free and unsupervised geometric deep learning frameworks (e.g., UGM2N, GNNRL-Smoothing) based on Graph Neural Networks and Reinforcement Learning to automate large mesh deformation and quality restoration.
GNNs Reinforcement Learning M-Uniform Loss Unsupervised
Mesh Quality Evaluation & Diagnosis
Designing high-fidelity, intelligent quality indicators for structured and unstructured grids, transforming geometric topology into graph representations to quantitatively forecast physical simulation stability.
Graph Indicator Quality Metrics Fine-grained Assessment
AI for Science & CFD Foundation Solvers
Accelerating aerodynamic shape optimization, exploring generalizable neural solvers for PDEs (e.g., LLM4Fluid, ST-PINN), and building intelligence-driven computational paradigms for complex fluid flows.
AI4S LLM for Physics PINNs Aerodynamic Design

📚 Selected Publications

2026 International Joint Conference on Neural Networks (IJCNN) (2026) CCF-C
Ke YANG, Xinhai CHEN, Zhichao WANG, Qinglin WANG, Jie LIU. A Fine-Grained Intelligent Mesh Quality Evaluation Algorithm Based on Neural Networks [C]// 2026 International Joint Conference on Neural Networks (IJCNN). 2026. (Accepted Mar 24, 2026, CCF-C)
Details
@article{wang2026afin,
  title     = { A Fine-Grained Intelligent Mesh Quality Evaluation Algorithm Based on Neural Networks },
  author    = { Zhichao Wang and colleagues },
  journal   = { 2026 International Joint Conference on Neural Networks (IJCNN) },
  year      = { 2026 }
}
Computers & Fluids (2026)
Pei J, Chen X, Liu Y, Wang Z, et al. Generalization-Aware Structured Mesh Smoothing via Graph Neural Networks[J]. Computers & Fluids, 2025: 106895. (CAS Q3, IF 3.0, Jan 30, 2026)
@article{wang2026gener,
  title     = { Generalization-Aware Structured Mesh Smoothing via Graph Neural Networks },
  author    = { Zhichao Wang and colleagues },
  journal   = { Computers & Fluids },
  year      = { 2026 },
  url       = { https://doi.org/10.1016/j.compfluid.2025.106895 }
}
arXiv:2601.21681 (2026) Preprint
Xiao Q, Chen X, Wang Q, Guo X, Wang B, Chen W, Wang Z, et al. LLM4Fluid: Large Language Models as Generalizable Neural Solvers for Fluid Dynamics[J]. arXiv:2601.21681, 2026.
@article{wang2026llm4f,
  title     = { LLM4Fluid: Large Language Models as Generalizable Neural Solvers for Fluid Dynamics },
  author    = { Zhichao Wang and colleagues },
  journal   = { arXiv:2601.21681 },
  year      = { 2026 },
  url       = { https://arxiv.org/abs/2601.21681 }
}
Neural Networks (2025) CCF-B CAS Q2 Top
Wang, Z., Chen X, Gong C, et al. GNNRL-Smoothing: A prior-free reinforcement learning model for mesh optimization[J]. Neural Networks, 2025: 108235. (CAS Q2 Top, CCF-B, IF 6.3, Oct 19, 2025)
@article{wang2025gnnrl,
  title     = { GNNRL-Smoothing: A prior-free reinforcement learning model for mesh optimization },
  author    = { Zhichao Wang and colleagues },
  journal   = { Neural Networks },
  year      = { 2025 },
  url       = { https://doi.org/10.1016/j.neunet.2025.108235 }
}
Advances in Neural Information Processing Systems (NeurIPS 2025) (2025) NeurIPS / CCF-A
Wang Z, Chen X, Wang Q, et al. UGM2N: An unsupervised and generalizable mesh movement network via M-uniform loss[C]. In Advances in Neural Information Processing Systems (NeurIPS 2025). (CCF-A, Sep 18, 2025)
@article{wang2025ugm2n,
  title     = { UGM2N: An Unsupervised and Generalizable Mesh Movement Network via M-Uniform Loss },
  author    = { Zhichao Wang and colleagues },
  journal   = { Advances in Neural Information Processing Systems (NeurIPS 2025) },
  year      = { 2025 },
  url       = { https://openreview.net/forum?id=UspcIEkK0y&referrer=%5BAuthor%20Console%5D(%2Fgroup%3Fid%3DNeurIPS.cc%2F2025%2FConference%2FAuthors%23your-submissions) }
}
Engineering Computations (2025)
Chen X, Wang Z, Liu Y, et al. A neural network approach for unstructured mesh quality evaluation[J]. Engineering Computations, 2025, 42(6): 2021-2035. (CAS Q4, IF 1.9, Jul 25, 2025)
@article{wang2025aneu,
  title     = { A neural network approach for unstructured mesh quality evaluation },
  author    = { Zhichao Wang and colleagues },
  journal   = { Engineering Computations },
  year      = { 2025 },
  url       = { https://doi.org/10.1108/EC-XX-XXXX-XXXX }
}
Frontiers of Information Technology & Electronic Engineering (2025) CCF-C
Wang Z, Chen X, Yan J, et al. An intelligent mesh-smoothing method with graph neural networks[J]. Frontiers of Information Technology & Electronic Engineering, 2025, 26(3): 367-384. (CAS Q4, CCF-C, IF 2.9, Apr 7, 2025)
@article{wang2025anin,
  title     = { An intelligent mesh-smoothing method with graph neural networks },
  author    = { Zhichao Wang and colleagues },
  journal   = { Frontiers of Information Technology & Electronic Engineering },
  year      = { 2025 },
  url       = { https://doi.org/10.1631/FITEE.2400123 }
}
Acta Aeronautica et Astronautica Sinica (2025) Top Aeronautical Journal
Wang Z, Chen X, Deng L, et al. A surface mesh smoothing method for aircraft based on unsupervised learning[J]. Acta Aeronautica et Astronautica Sinica, 2025, 46(10): 631172. (EI Indexed, Top Journal in Aeronautics, Feb 6, 2025)
Details
@article{wang2025asur,
  title     = { A surface mesh smoothing method for aircraft based on unsupervised learning },
  author    = { Zhichao Wang and colleagues },
  journal   = { Acta Aeronautica et Astronautica Sinica },
  year      = { 2025 }
}
Engineering Applications of Computational Fluid Mechanics (2024) CAS Q1 Top
Chen X, Wang Z, Deng L, et al. Towards a new paradigm in intelligence-driven computational fluid dynamics simulations[J]. Engineering Applications of Computational Fluid Mechanics, 2024, 18(1): 2407005. (CAS Q1 Top, IF 5.4, Sep 25, 2024)
@article{wang2024towar,
  title     = { Towards a new paradigm in intelligence-driven computational fluid dynamics simulations },
  author    = { Zhichao Wang and colleagues },
  journal   = { Engineering Applications of Computational Fluid Mechanics },
  year      = { 2024 },
  url       = { https://doi.org/10.1080/19942060.2024.2407005 }
}
International Journal of Modern Physics C (2024)
Li T, Yan J, Chen X, Wang Z, et al. Accelerating aerodynamic design optimization based on graph convolutional neural network[J]. International Journal of Modern Physics C, 2024, 35(01): 2450007. (CAS Q4, IF 1.6)
Details
@article{wang2024accel,
  title     = { Accelerating aerodynamic design optimization based on graph convolutional neural network },
  author    = { Zhichao Wang and colleagues },
  journal   = { International Journal of Modern Physics C },
  year      = { 2024 }
}
2023 International Joint Conference on Neural Networks (IJCNN) (2023) CCF-C
Yan J, Chen X, Wang Z, et al. ST-PINN: A self-training physics-informed neural network for partial differential equations[C]// 2023 International Joint Conference on Neural Networks (IJCNN). IEEE, 2023: 1-8. (CCF-C, EI)
Details
@article{wang2023st-pi,
  title     = { ST-PINN: A self-training physics-informed neural network for partial differential equations },
  author    = { Zhichao Wang and colleagues },
  journal   = { 2023 International Joint Conference on Neural Networks (IJCNN) },
  year      = { 2023 }
}
Entropy (2022)
Chen X, Wang Z, Liu J, et al. A neural network-based mesh quality indicator for three-dimensional cylinder modelling[J]. Entropy, 2022, 24(9): 1245. (CAS Q3, IF 2.0, Sep 4, 2022)
@article{wang2022aneu,
  title     = { A neural network-based mesh quality indicator for three-dimensional cylinder modelling },
  author    = { Zhichao Wang and colleagues },
  journal   = { Entropy },
  year      = { 2022 },
  url       = { https://doi.org/10.3390/e24091245 }
}
Engineering with Computers (2022) CAS Q2 Top
Wang Z, Chen X, Li T, et al. Evaluating mesh quality with graph neural networks[J]. Engineering with Computers, 2022, 38(5): 4663-4673. (CAS Q2 Top, IF 4.9, Jul 30, 2022)
@article{wang2022evalu,
  title     = { Evaluating mesh quality with graph neural networks },
  author    = { Zhichao Wang and colleagues },
  journal   = { Engineering with Computers },
  year      = { 2022 },
  url       = { https://doi.org/10.1007/s00366-021-01487-6 }
}

Explore Full Publications List →

💼 Experience & Education

  • Assistant Professor
    School of Artificial Intelligence and Automation, Huaiyin Normal University (HYTC), Huaian, China | 2026.09 – Present
  • Ph.D. in Computer Science and Technology
    National University of Defense Technology (NUDT), Changsha, China | 2023 – 2026
  • M.S. in Electronic Information
    National University of Defense Technology (NUDT), Changsha, China | 2020 – 2022
  • B.S. in Mechatronic Engineering
    Northwestern Polytechnical University (NWPU), Xi'an, China | 2016 – 2020

🏆 Honors and Awards

  • University-level Outstanding Student
    National University of Defense Technology, 2025
  • Second-class Academic Scholarship
    National University of Defense Technology, 2025
  • College-level Outstanding Student
    College of Computer, National University of Defense Technology, 2025
  • National Scholarship (Top 1%)
    Ministry of Education of PRC & Northwestern Polytechnical University, 2017

🤝 Academic Activities & Service

Invited Journal Reviewer:

  • Computer Methods in Applied Mechanics and Engineering (CMAME)
  • Neural Networks
  • Aerospace Science and Technology (AST)
  • Engineering Applications of Artificial Intelligence (EAAI)
  • Simulation Modelling Practice and Theory (SMPT)

Conference Presentations & Attendance:

  • Oral Presentation: The 1st National Conference on Intelligent Fluid Mechanics, 2024
  • Oral Presentation: The 2023 National Workshop on Mesh Generation and Applications (MEGAS 2023), 2023
  • Attendance: The 2nd Chinese Conference of Aerodynamics, 2023

Teaching Assistant:

  • University Computing course, National University of Defense Technology, 2024 & 2025