| 职称：副研究员，硕导 |
办公室：东南大学九龙湖校区悠谷4号楼 | |
办公电话：17766100836 | |
Email：jiananzhang@seu.edu.cn | |
学习经历： | |
2015年9月– 2020年加拿大卡尔顿大学，电子与计算机工程，博士 2013年9月– 2020年天津大学，电磁场与微波技术，博士 2009年9月– 2013年7月天津大学，电子信息工程，学士 | |
工作经历: | |
2020年1月– 2021年12月卡尔顿大学，电子系，助理研究员（合作导师：张齐军教授，加拿大工程院院士、工程研究院院士，IEEE Fellow） 2022年1月 – 至今东南大学，信息科学与工程学院、毫米波国家重点实验室，副研究员，“紫金学者” | |
教授课程: | |
《数字电路与系统》 | |
研究方向： | |
智能电磁优化：机器学习辅助的微波器件建模、超表面逆向设计、成品率优化 智能电磁计算：物理约束深度学习、有限元电磁仿真及设计优化、电磁灵敏度分析 量子计算：量子计算在求解电磁问题中的应用 | |
学术兼职： | |
国际研讨会主席（General Chair）： 2022 International Young Professionals Workshop on Electromagnetic Modeling and Optimization (EMO 2021) 国际知名期刊审稿人： IEEE Transactions on Microwave Theory and Techniques IEEE Microwave Wireless Components Letters IEEE International Journal of RF and Microwave Computer-Aided-Engineering | |
代表性学术成果： | |
学术论文： [1] J. Zhang, J. W. You, F Feng, W. Na, Z. C. Lou, Q. J. Zhang, T. J. Cui, “Physics-driven machine-learning approach incorporating temporal coupled mode theory for intelligent design of metasurfaces”, IEEE Trans. Microw. Theory Techn., 2023, doi: 10.1109/tmtt.2023.3238076. [2] J. Zhang, S. Yan, F. Feng, J. Jin, W. Zhang, J. Wang, Q. J. Zhang, “A novel surrogate-based approach to yield estimation and optimization of microwave structures using combined quadratic mappings and matrix transfer functions,” IEEE Trans. Microw. Theory Techn.,, 2022, 70(8): 3802-3816. [3] J. Zhang, F. Feng, J. Jin, and Q. J. Zhang, “Adaptively weighted yield-driven EM optimization incorporating neuro-transfer function surrogate with applications to microwave filters,” IEEE Trans. Microw. Theory Techn., vol. 69, no. 1, pp. 518-528, Jan. 2021. [4] J. Zhang, F. Feng, W. Zhang, J. Jin, J. Ma, and Q. J. Zhang, “A novel training approach for parametric modeling of microwave passive components using Pade via Lanczos and EM sensitivities,” IEEE Trans. Microw. Theory Techn., vol. 68, no. 6, pp. 2215-2233, Jun. 2020. [5] J. Zhang, C. Zhang, F. Feng, W. Zhang, J. Ma, and Q. J. Zhang, “Polynomial chaos-based approach to yield-driven EM optimization,” IEEE Trans. Microw. Theory Techn., vol. 66, no. 7, pp. 3186-3199, Jul. 2018.（入选IEEE TMTT Popular Articles） [6] J. Zhang, J. Chen, Q. Guo, W. Liu, F. Feng, and Q. J. Zhang, “Parameterized modeling incorporating MOR-based rational transfer functions with neural networks for microwave components,” IEEE Microw. Wireless Compon. Lett., vol. 32, no. 5, pp. 379-382, May 2022. [7] J. Zhang, F. Feng, and Q. J. Zhang, “Rapid yield estimation of microwave passive components using model-order reduction based neuro-transfer function models,” IEEE Microw. Wireless Compon. Lett., vol. 31, no. 4, pp. 333-336, Apr. 2021.（入选IEEE MWCL Popular Articles） [8] J. Zhang, F. Feng, J. Jin, and Q. J. Zhang, “Efficient yield estimation of microwave structures using mesh deformation-incorporated space mapping surrogates,” IEEE Microw. Wireless Compon. Lett., vol. 30, no. 10, pp. 937-940, Oct. 2020.（入选IEEE MWCL Popular Articles） [9] J. Cui, F. Feng, J. Zhang*, L. Zhu, and Q. J. Zhang, “Bayesian-assisted multilayer neural network structure adaptation method for microwave design,” IEEE Microw. Wireless Compon. Lett., vol. 33, no. 1, pp. 3-6, Jan. 2023. [10] J. Zhang, F. Feng, W. Na, S. Yan, and Q. J. Zhang, “Parallel space mapping based yield-driven EM optimization incorporating trust region algorithm and polynomial chaos expansion,” IEEE Access, vol. 7, no. 1, pp. 143673-143683, Sept. 2019. [11] F. Feng, J. Xue, J. Zhang*，M. Li, W. Liu, and Q. J. Zhang, “Concise and compatible MOR-based self-adjoint EM sensitivity analysis for fast frequency sweep,” accepted, IEEE Trans. Microw. Theory Techn., Feb. 2023. [12] F. Feng, J. Zhang, J. Jin, W. Na, S. Yan, and Q. J. Zhang, “Efficient FEM-based EM optimization technique using combined Lagrangian method with Newton's method, IEEE Trans. Microw. Theory Techn., vol. 68, no. 6, pp.2194-2205, Jun. 2020. [13] F. Feng, J. Zhang, J. Jin, W. Zhang, Z. Zhao, and Q. J. Zhang, Adjoint EM sensitivity analysis for fast frequency sweep using Matrix Pade via Lanczos technique based on finite element method, IEEE Trans. Microw. Theory Techn., vol. 69, no. 5, pp. 2413-2428, Mar. 2021. [14] F. Feng, J. Zhang, W. Zhang, Z. Zhao, J. Jin, and Q. J. Zhang, Coarse- and fine-mesh space mapping for EM optimization incorporating mesh deformation, IEEE Microw. Wireless Compon. Lett., vol. 29, no. 8, pp. 510-512, Aug. 2019. [15] F. Feng, J. Zhang, W. Zhang, Z. Zhao, J. Jin, and Q. J. Zhang, Recent advances in parametric modeling of microwave components using combined neural network and transfer function, International Journal of Numerical Modelling: Electronic Networks, Devices and Fields, vol. 33, no. 6, pp. 1-17, Nov. 2020.
书籍章节： [1] F. Feng#, J. Zhang#（共同一作）, and Q. J. Zhang, Application of artificial neural networks for design optimization under uncertainty for microwave structures, Institute of Engineering and Technology (IET) press, 2021. [2] F. Feng, J. Zhang, W. Na, J. Jin, and Q. J. Zhang, Parametric modeling of microwave components using combined neural network and transfer function, World Scientific, 2020. 专利： [1]一种用于超表面智能设计的物理驱动机器学习方法, 2022-10-11, 中国, 受理号：CN202211239682.2 [2]一种用于求解电磁有限元方程的量子方法, 2022-11-15, 中国, 受理号：CN202211425125.X [3]电磁场有限元快速频率分析的电磁灵敏度分析方法, 2021-8-27, 中国, 受理号：CN202110992300.2
科研项目： (1) 江苏省科学技术厅, 基础研究计划自然科学基金-青年基金项目, BK20220808, 面向高频微波器件成品率驱动设计的先进统计建模和优化技术, 2022-07 至今, 20万元, 在研, 主持。 (2) JWKJW，JWKJW基础加强项目课题，N/A，全空域****， 2022-8-1 至 2026-8-21，420万元，在研，参与。 | |
欢迎对智能优化算法、机器学习、计算电磁学、量子计算等方向感兴趣的本科同学加入课题组进行科研训练和毕业设计！课题组常年招收硕士、博士研究生，欢迎报考，并提供机会至国外知名大学交流访问！ | |
