金晶，女，博士，副研究员，硕士生导师。2014年获武汉大学电子信息工程专业学士学位，2021年获天津大学微电子学与固体电子学专业和加拿大卡尔顿大学电子与计算机工程专业双博士学位。从事微波器件/电路建模与优化设计方向的研究工作，研究领域包括人工神经网络建模技术、电子设计自动化（EDA）算法、深度学习、计算电磁学仿真与快速优化设计、电磁拓扑优化方法等。近五年发表相关学术论文和著作章节共30余篇，其中发表于微波领域顶级期刊IEEE Transactions on Microwave Theory and Techniques（IEEE TMTT, 中科院一区Top）的高水平学术论文10余篇，主持武汉市科技局知识创新专项课题，参与中央高校基本科研业务费交叉科学研究项目和国防科工局鸿鹊创新基金课题，担任IEEE TMTT， IEEE NNLS等著名期刊独立审稿人。
近五年代表性论文
[1] J. Jin, F. Feng, J. Zhang, J. Ma and Q. -J. Zhang, "Efficient EM Topology Optimization Incorporating Advanced Matrix Padé Via Lanczos and Genetic Algorithm for Microwave Design," in IEEE Transactions on Microwave Theory and Techniques, vol. 69, no. 8, pp. 3645-3666, Aug. 2021. (中科院一区Top)
[2] J. Jin, F. Feng, W. Na, J. Zhang, W. Zhang, Z. Zhao, Q.-J. Zhang, "Advanced Cognition-Driven EM Optimization Incorporating Transfer Function-Based Feature Surrogate for Microwave Filters," in IEEE Transactions on Microwave Theory and Techniques, vol. 69, no. 1, pp. 15-28, Jan. 2021. (中科院一区Top)
[3] J. Jin, C. Zhang, F. Feng, W. Na, J. Ma and Q. Zhang, "Deep Neural Network Technique for High-Dimensional Microwave Modeling and Applications to Parameter Extraction of Microwave Filters," in IEEE Transactions on Microwave Theory and Techniques, vol. 67, no. 10, pp. 4140-4155, Oct. 2019. (中科院一区Top)
[4] F. Feng, W. Na, J. Jin, J. Zhang, W. Zhang and Q. -J. Zhang, "Artificial Neural Networks for Microwave Computer-Aided Design: The State of the Art," in IEEE Transactions on Microwave Theory and Techniques, vol. 70, no. 11, pp. 4597-4619, Nov. 2022. (中科院一区Top)
[5] F. Feng, W. Na, J. Jin, W. Zhang and Q. -J. Zhang, "ANNs for Fast Parameterized EM Modeling: The State of the Art in Machine Learning for Design Automation of Passive Microwave Structures," in IEEE Microwave Magazine, vol. 22, no. 10, pp. 37-50, Oct. 2021.
[6] J. Jin, F. Feng, J. Zhang, S. Yan, W. Na and Q. Zhang, "A Novel Deep Neural Network Topology for Parametric Modeling of Passive Microwave Components," in IEEE Access, vol. 8, pp. 82273-82285, 2020.
[7] Jin, J, Feng, F, Na, W, et al. Recent advances in neural network-based inverse modeling techniques for microwave applications. Int J Numer Model El. 2020; 33:e2732.
课题组研究基础扎实，并与国内外多所大学建立了良好的合作关系，欢迎对相关研究感兴趣的同学报考本课题组的研究生。
办公地址：华中师范大学9号楼512办公室
Email: jingjin@ccnu.edu.cn
