姓名：张宇隆
性别：男
职称：副教授，硕导
学位：博士
电子邮件： zhangyl@fzu.edu.cn
研究方向：工业缺陷检测，迁移学习，多模态大模型，生成模型
学术主页： 谷歌学术
教育工作经历
2025.8~至今 福州大学 电气工程与自动化学院(自动化系) 副教授
2020.9~2025.6 浙江大学 控制科学与工程学院 博士
2016.9~2020.6 福州大学 电气工程与自动化学院 学士
代表性论文
[1] Y. Zhang, Y. Yao, S. Chen, P. Jin, Y. Zhang, J. Jin, J. Lu. Rethinking Guidance Information to Utilize Unlabeled Samples: A Label Encoding Perspective. International Conference on Machine Learning (ICML 2024). (CCF-A类)
[2] Y. Zhang, S. Chen, W. Jiang, Y. Zhang, J. Lu, J. T. Kwok. Domain-Guided Conditional Diffusion Model for Unsupervised Domain Adaptation. Neural Networks, 2025.
[3] Z. Zhuang*, Y. Zhang*, X. Wang, J. Lu, Y. Wei, and Y. Zhang. Time-Varying LoRA: Towards Effective Cross-Domain Fine-Tuning of Diffusion Models. Neural Information Processing Systems (NeurIPS 2024). (CCF-A类)
[4] Y. Zhang, Y. Wang, Z. Jiang, F. Liao, L. Zheng, D. Tan, J. Chen, and J. Lu. Diversifying Tire-Defect Image Generation Based on Generative Adversarial Network. IEEE Transactions on Instrumentation and Measurement, 2022.
[5] Z. Chen, Y. Zhang, O. Zhang, F. Wang, L. Yao, H. Wang, Z. Song. Blending Data and Knowledge for Process Industrial Modeling Under Riemannian Preconditioned Bayesian Framework. IEEE Transactions on Knowledge and Data Engineering, 2025. (CCF-A类)
[6] Y. Zhang, Y. Wang, Z. Jiang, L. Zheng, J. Chen, and J. Lu. Domain Adaptation via Transferable Swin Transformer for Tire Defect Detection. Engineering Applications of Artificial Intelligence, 2023.
[7] Y. Zhang, Y. Wang, Z. Jiang, L. Zheng, J. Chen, and J. Lu. Subdomain Adaptation Network with Category Isolation Strategy for Tire Defect Detection. Measurement, 2022.
[8] Y. Zhang, Y. Wang, Z. Jiang, L. Zheng, J. Chen, and J. Lu. Tire Defect Detection by Dual Domain Adaptation-Based Transfer Learning Strategy. IEEE Sensors Journal, 2022.
[9] Y. Zhang, Y. Wang, Z. Jiang, L. Zheng, J. Chen, and J. Lu. A Novel Class-Level Weighted Partial Domain Adaptation Network for Defect Detection. Applied Intelligence, 2023.
[10] Z. Zhuang, X. Wang, W. Li, Y. Zhang, …, and Y. Wei. Come Together, But Not Right Now: A Progressive Strategy to Boost Low-Rank Adaptation. International Conference on Machine Learning (ICML 2025). (CCF-A类)
* 他引共164次，截止2025年10月
代表性发明专利
[1] 张宇隆, 陈金水, 卢建刚. 基于可迁移Swin Transformer的轮胎瑕疵检测域自适应方法. 发明专利，CN115330697A.
[2] 卢建刚, 张宇隆, 陈金水. 基于自注意力机制与双重领域自适应的轮胎瑕疵检测方法及模型. 发明专利，ZL202111460037.9.
[3] 卢建刚, 张宇隆, 陈金水. 基于多重表示与多重子域自适应的轮胎瑕疵检测方法. 发明专利，ZL202210071489.6.
[4] 徐哲壮, 张宇隆, 王荣凯, 刘安国. 基于多邻居节点RSSI差异的移动设备邻近无线节点的估计方法. 发明专利，ZL201910187929.2.
获奖情况
[1] 2025年 浙江大学优秀毕业生
[2] 2021-2025年 浙江大学优秀研究生
[3] 2019年 国家奖学金
[4] 2019年 福州大学十佳大学生
[5] 2020年 福州大学优秀毕业生
学术服务
Artificial Intelligence, International Conference on Machine Learning (ICML), Neural Information Processing Systems (NeurIPS), IEEE Transactions on Instrumentation and Measurement (TIM), Engineering Applications of Artificial Intelligence (EAAI)等期刊审稿人
实验室纳新
希望招收对工业缺陷检测、深度学习、机器视觉感兴趣，勤奋好学、编程能力强的同学
