副教授

副教授

张志仲
副教授,博士生导师

研究方向:AI+EDA, 科学agent

邮箱:zhangzhizhong@buaa.edu.cn

教师个人主页
基本情况

教育经历:

2011-2015 det365在线登录 信息与计算科学 本科

2015-2022 det365在线登录 微电子学与固体电子学 博士

2019-2022 Université Paris-Saclay 物理学 博士

工作经历:

2022-2024 det365在线登录 博士后

2024至今 det365在线登录 副教授

主讲课程

本科生课程:应用概率与统计

研究生课程:工程数值方法与优化

研究方向

AI+EDA, 科学agent

教学科研成果

获奖情况:

无

发明专利:

[1] 张悦; 张志仲; 赵巍胜 温度传感器、组件及温度测量方法 ZL201910515151.3

代表性论文:

[1] Xu, S., Zhang, Z., Dai, B., Huang, Y., Pang, Y., Ma, Y., Lou, W., Wang, T., Liu, C., Yang, M., Tang, M., Cheng, H., Wang, K. L., Chang, K., Zhang, Y., Zhao, W., & Zhang, X. (2026). Ultralong octupole moment switching driven by twin topological spin structures. Nature Communications, 17(1), Article 2503.

[2] Feng, X., Zhang, Z., Xie, Y., Zheng, Z., Wang, J., Song, Z., Yang, B., Lin, K., Liu, G., He, Y., Li, B., Zhao, W., & Zhang, Y. (2026). Field-Free Electrical Switching of Perpendicular Magnetization via Domain-Wall-Free Textures in Ferrimagnets. Physical Review Letters, 136(12), Article 126701.

[3] Zhang, Z., Sun, X., Sun, J., Sun, Y., Cui, M., Wang, X., Xie, J., Zhang, H., Li, X., Cao, K., Wang, G., Liu, H., Zhao, W., & Zhang, Y. (2025). Confidence-Aware AI-Driven Full-Chain Simulation and Material-to-System Co-Optimization of Spin-CMOS Hybrid Circuits. In 2025 IEEE International Electron Devices Meeting, IEDM 2025 (Technical Digest - International Electron Devices Meeting, IEDM). Institute of Electrical and Electronics Engineers Inc..

[4] Zhang, Z., Lin, K., Cao, K., Wang, J., Yang, J., Zhang, B., Zhang, H., Liu, H., Wang, G., Zhao, W., & Zhang, Y. (2024). A Production Line Level MTJ Modeling Framework: Integrating Physical Mechanisms, Experimental Data and Manufacturing Variation. In 2024 IEEE International Electron Devices Meeting, IEDM 2024 (Technical Digest - International Electron Devices Meeting, IEDM). Institute of Electrical and Electronics Engineers Inc..

[5] Zhang, Z., Lin, K., Zhang, Y., Bournel, A., Xia, K., Kläui, M., & Zhao, W. (2023). Magnon scattering modulated by omnidirectional hopfion motion in antiferromagnets for meta-learning. Science Advances, 9(6), Article eade7439.

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