📝 Publications
✒️ Journal Paper
First/Corresponding-author Publications
I-J-9Shan Tao, Li Maokun, Yang Fan, Xu Shenheng and Su Donglin, Complex-valued Neural Operator for Solving 2D Wave Equation Based on Graph Neural Network, IEEE Transactions on Antennas and Propagation, doi: 10.1109/TAP.2025.3609818.I-J-8Shan Tao, Li Maokun, Yang Fan and Xu Shenheng, Solving Combined Field Integral Equations with Physics-informed Graph Residual Learning for EM Scattering of 3D PEC Targets, IEEE Transactions on Antennas and Propagation, doi: 10.1109/TAP.2023.3331262.I-J-7Shan Tao, Zen Jinhong, Song Xiaoqian, Li Maokun, et al., Physics-informed Supervised Residual Learning for Electromagnetic Modeling, IEEE Transactions on Antennas and Propagation, doi: 10.1109/TAP.2023.3245281.I-J-6Shan Tao, Lin Zhichao, Song Xiaoqian, Li Maokun, et al., Physics-informed Supervised Residual Learning for 2D Inverse Scattering Problem, IEEE Transactions on Antennas and Propagation, doi: 10.1109/TAP.2023.3242372.I-J-5Shan Tao, Lin Zhichao, Song Xiaoqian, Li Maokun, et al., Neural Born Iterative Method For Solving Inverse Scattering Problems: 2D Cases, IEEE Transactions on Antennas and Propagation, 2022, doi: 10.1109/TAP.2022.3217333.I-J-4Shan Tao, Guo Rui, Li Maokun, et al., Application of Multitask Learning for 2-D Modeling of Magnetotelluric Surveys: TE Case, IEEE Transactions on Geoscience and Remote Sensing, vol. 60, pp. 1-9, 2022, Art no. 4503709, doi: 10.1109/TGRS.2021.3101119.I-J-3Shan Tao, Pan Xiaotian, Li Maokun, et al., Coding programmable metasurfaces based on deep learning techniques, IEEE Journal on Emerging and Selected Topics in Circuits and Systems, vol. 10, no. 1, pp. 114-125, March 2020, doi: 10.1109/JETCAS.2020.2972764.I-J-2Shan Tao, Li Maokun, et al., Phase Synthesis of Beam-Scanning Reflectarray Antenna Based on Deep Learning Technique, Progress In Electromagnetics Research, Vol. 172, 41-49, 2021, doi:10.2528/PIER21091307.I-J-1Shan Tao, Tang Wei, Dang Xunwang, Li Maokun, et al., Study on a fast solver for Poisson’s equation based on deep learning technique, IEEE Transactions on Antennas and Propagation, vol. 68, no. 9, pp. 6725-6733, Sept. 2020, doi: 10.1109/TAP.2020.2985172.
Co-Authored Publications
C-J-6Liu Daoqi, Shan Tao, Li Maokun, Yang Fan and Xu Shenheng, Multi-Frequency Neural Born Iterative Method for Solving 2-D Inverse Scattering Problems, IEEE Transactions on Computational Imaging, vol. 11, pp. 1243-1257, 2025, doi: 10.1109/TCI.2025.3607150.C-J-5Cao Huilin; Sun Haoran, Liang Jingwei, Shan Tao, Ren Yuxiang and Maokun Li, Physics-Data Hybrid Driven Edge-Featured Graph Attention Networks for Surface Currents Learning of 3D PEC Targets, IEEE Transactions on Antennas and Propagation, doi: 10.1109/TAP.2025.3602467.C-J-4Salucci M, Arrebola M, Shan Tao and Li M, Artificial Intelligence: New Frontiers in Real-Time Inverse Scattering and Electromagnetic Imaging, IEEE Transactions on Antennas and Propagation, vol. 70, no. 8, pp. 6349-6364, Aug. 2022, doi: 10.1109/TAP.2022.3177556.C-J-3Guo R, Shan Tao et al., Physics Embedded Deep Neural Network for Solving Volume Integral Equation: 2-D Case, in IEEE Transactions on Antennas and Propagation, vol. 70, no. 8, pp. 6135-6147, Aug. 2022, doi: 10.1109/TAP.2021.3070152.C-J-2Guo R, Lin Z, Shan Tao, et al., Physics Embedded Deep Neural Network for Solving Full-Wave Inverse Scattering Problems, in IEEE Transactions on Antennas and Propagation, vol. 70, no. 8, pp. 6148-6159, Aug. 2022, doi: 10.1109/TAP.2021.3102135.C-J-1Guo R, Lin Z, Shan Tao, et al., Solving Combined Field Integral Equation With Deep Neural Network for 2-D Conducting Object, IEEE Antennas and Wireless Propagation Letters, vol. 20, no. 4, pp. 538-542, April 2021, doi: 10.1109/LAWP.2021.3056460.
🏷️ Conference Paper
First/Corresponding-author Publications
I-C-6Shan Tao, Solving Electromagnetic Scattering of 3D PEC Targets Based on Graph Neural Networks, 2024 International Applied Computational Electromagnetics Society Symposium (ACES-China), Xi’an, China, 2024, pp. 1-2, doi: 10.1109/ACES-China62474.2024.10699762.I-C-5Shan Tao, Li M, Yang F and Xu S, Hardware-friendly Unsupervised Coding Scheme for Reconfigurable Intelligent Surface Based on Binary Neural Networks, 2022 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting (AP-S/URSI), 2022, pp. 449-450, doi: 10.1109/APS/USNC-URSI47032.2022.9887254.I-C-4Shan Tao, Lin Z, Song X, et al. A New Approach for Solving Inverse Scattering Problems Based on Physics informed Supervised Residual Learning, 2022 16th European Conference on Antennas and Propagation (EuCAP). IEEE, 2022: 1-4.I-C-3Shan Tao, Song X, Guo R, et al. Physics-informed Supervised Residual Learning for Electromagnetic Modeling, 2021 International Applied Computational Electromagnetics Society Symposium (ACES). IEEE, 2021: 1-4.I-C-2Shan Tao, Li M, Xu S, et al. Synthesis of reflectarray based on deep learning technique, 2018 Cross Strait Quad-Regional Radio Science and Wireless Technology Conference (CSQRWC). IEEE, 2018: 1-2.I-C-1Shan Tao, Dang X, Li M, et al. Study on a 3D Possion’s equation slover based on deep learning technique, 2018 IEEE International Conference on Computational Electromagnetics (ICCEM). IEEE, 2018: 1-3.
Co-Authored Publications
C-C-3Zeng J, Shan Tao, Li M, et al. Neural Contrast Source Inversion Method Based on Single-frequency Data, 2022 International Applied Computational Electromagnetics Society (ACES-China) Symposium (accepted)C-C-2Shao T, Shan Tao, Li M, et al. A Poisson’s Equation Solver Based on Neural Network Precondtioned CG Method, 2022 International Applied Computational Electromagnetics Society (ACES-China) Symposium (accepted)C-C-1Tang W, Shan Tao, Dang X, et al. Study on a Poisson’s equation solver based on deep learning technique, 2017 IEEE Electrical Design of Advanced Packaging and Systems Symposium (EDAPS). IEEE, 2017: 1-3.