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
📚 Selected Publications
@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 }
}@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 }
}@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 }
}@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 }
}@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) }
}@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 }
}@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 }
}@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 }
}@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 }
}@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 }
}@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 }
}@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 }
}@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 ProfessorSchool of Artificial Intelligence and Automation, Huaiyin Normal University (HYTC), Huaian, China | 2026.09 – Present
- Ph.D. in Computer Science and TechnologyNational University of Defense Technology (NUDT), Changsha, China | 2023 – 2026
- M.S. in Electronic InformationNational University of Defense Technology (NUDT), Changsha, China | 2020 – 2022
- B.S. in Mechatronic EngineeringNorthwestern Polytechnical University (NWPU), Xi'an, China | 2016 – 2020
🏆 Honors and Awards
- University-level Outstanding StudentNational University of Defense Technology, 2025
- Second-class Academic ScholarshipNational University of Defense Technology, 2025
- College-level Outstanding StudentCollege 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