| 2025 | AAAI | AeroGTO: An Efficient Graph-Transformer Operator for Learning Large-Scale Aerodynamics of 3D Vehicle Geometries. | Pengwei Liu, Pengkai Wang, Xingyu Ren, Hangjie Yuan, Zhongkai Hao, Chao Xu, Shengze Cai, Dong Ni |
| 2025 | ICML | Accelerating PDE-Constrained Optimization by the Derivative of Neural Operators. | Ze Cheng, Zhuoyu Li, Xiaoqiang Wang, Jianing Huang, Zhizhou Zhang, Zhongkai Hao, Hang Su |
| 2024 | ICLR | Accelerating Data Generation for Neural Operators via Krylov Subspace Recycling. | Hong Wang, Zhongkai Hao, Jie Wang, Zijie Geng, Zhen Wang, Bin Li, Feng Wu |
| 2024 | ICML | Reference Neural Operators: Learning the Smooth Dependence of Solutions of PDEs on Geometric Deformations. | Ze Cheng, Zhongkai Hao, Xiaoqiang Wang, Jianing Huang, Youjia Wu, Xudan Liu, Yiru Zhao, Songming Liu, Hang Su |
| 2024 | ICML | DPOT: Auto-Regressive Denoising Operator Transformer for Large-Scale PDE Pre-Training. | Zhongkai Hao, Chang Su, Songming Liu, Julius Berner, Chengyang Ying, Hang Su, Anima Anandkumar, Jian Song, Jun Zhu |
| 2024 | ICML | PAPM: A Physics-aware Proxy Model for Process Systems. | Pengwei Liu, Zhongkai Hao, Xingyu Ren, Hangjie Yuan, Jiayang Ren, Dong Ni |
| 2024 | ICML | Improved Operator Learning by Orthogonal Attention. | Zipeng Xiao, Zhongkai Hao, Bokai Lin, Zhijie Deng, Hang Su |
| 2023 | ICLR | Equivariant Energy-Guided SDE for Inverse Molecular Design. | Fan Bao, Min Zhao, Zhongkai Hao, Peiyao Li, Chongxuan Li, Jun Zhu |
| 2023 | ICLR | Bi-level Physics-Informed Neural Networks for PDE Constrained Optimization using Broyden's Hypergradients. | Zhongkai Hao, Chengyang Ying, Hang Su, Jun Zhu, Jian Song, Ze Cheng |
| 2023 | ICML | GNOT: A General Neural Operator Transformer for Operator Learning. | Zhongkai Hao, Zhengyi Wang, Hang Su, Chengyang Ying, Yinpeng Dong, Songming Liu, Ze Cheng, Jian Song, Jun Zhu |
| 2023 | ICML | NUNO: A General Framework for Learning Parametric PDEs with Non-Uniform Data. | Songming Liu, Zhongkai Hao, Chengyang Ying, Hang Su, Ze Cheng, Jun Zhu |
| 2023 | ICML | MultiAdam: Parameter-wise Scale-invariant Optimizer for Multiscale Training of Physics-informed Neural Networks. | Jiachen Yao, Chang Su, Zhongkai Hao, Songming Liu, Hang Su, Jun Zhu |
| 2023 | IJCAI | On the Reuse Bias in Off-Policy Reinforcement Learning. | Chengyang Ying, Zhongkai Hao, Xinning Zhou, Hang Su, Dong Yan, Jun Zhu |
| 2022 | ICIP | AVT: Au-Assisted Visual Transformer for Facial Expression Recognition. | Rijin Jin, Sirui Zhao, Zhongkai Hao, Yifan Xu, Tong Xu, Enhong Chen |
| 2022 | ICML | GSmooth: Certified Robustness against Semantic Transformations via Generalized Randomized Smoothing. | Zhongkai Hao, Chengyang Ying, Yinpeng Dong, Hang Su, Jian Song, Jun Zhu |
| 2022 | IJCAI | Cluster Attack: Query-based Adversarial Attacks on Graph with Graph-Dependent Priors. | Zhengyi Wang, Zhongkai Hao, Ziqiao Wang, Hang Su, Jun Zhu |
| 2020 | KDD | ASGN: An Active Semi-supervised Graph Neural Network for Molecular Property Prediction. | Zhongkai Hao, Chengqiang Lu, Zhenya Huang, Hao Wang, Zheyuan Hu, Qi Liu, Enhong Chen, Cheekong Lee |