工业人工智能、基于信号处理和计算机视觉的模式识别、系统识别、及人智交互等领域
背景介绍
赵一帆，宁波东方理工大学力学与机械工程学院讲席教授，英国皇家工程院工业会士，英国高等教育学会会士，2025入选国家级高层次人才计划。曾任英国克兰菲尔德大学航空、交通与制造学院终身教授、博士生导师，担任全生命周期工程服务实验室主任。2000年与2003年分别获得北京理工大学自动控制专业学士和硕士学位，2007年获得英国谢菲尔德大学自动控制与系统工程博士学位。累计发表高水平学术论文200余篇，其中包含IEEE Transactions顶刊论文30余篇，以及CVPR、MICCAI、CIRP等国际顶级会议论文。出版学术专著6部，获授权国际专利3项。已培养博士后6人、博士研究生20余人、硕士研究生80余人，国际访问学者10名。主持和参与多项英国工程与自然科学研究理事会、英国皇家工程院、英国创新署以及空客和捷豹路虎等国际头部企业资助的重大科研项目，累计经费逾8000万元人民币。在知识转化方面，其研究成果已成功应用于飞机设计与运维、智能制造、自动驾驶以及智慧建造等领域。
教育背景
2003-2006：博士（自动控制和系统工程），英国谢菲尔德大学控制系
2000-2003：硕士（控制理论和控制工程），北京理工大学机电控制工程学院
1996-2000：学士（控制理论和控制工程），北京理工大学机电控制工程学院
工作经历
2026-至今：宁波东方理工大学，讲席教授
2023-2026：英国克兰菲尔德大学，终身教授
2019-2023：英国克兰菲尔德大学，副教授
2013-2019：英国克兰菲尔德大学，助理教授
2007-2013：英国谢菲尔德大学，助理研究员/研究员
学术兼职
2022-至今：副主编，Space: Science & Technology
2021-至今：副主编，中国机械工程学报
2023-至今：副主编，Bioengineering
2024-至今：西安电子科技大学创新引智基地学术委员会海外专家
2020-2023: 中国医科大学客座教授
获奖情况及荣誉
2025：入选斯坦福—爱思唯尔全球前 2% 顶尖科学家榜单
2023：《The Engineer》杂志“协作创新奖”
2021：中国国家留学基金管理委员会“国家优秀自费留学生导师奖“
2019：英国海洋工程、科学与技术学会丹尼奖章
2019：在《Automatica》发表的论文获捷克科学院最佳论文奖
2019：英国高等教育学院会士
总体情况
200余篇论文
Google Scholar：
https://scholar.google.com/citations?user=I-Hs9twAAAAJ&hl=en
代表作（*表示通讯作者）
[1]. Xie, W., Caglar, H., Deng, K., Ayre, D., & Zhao, Y*. (2026). LayupFormer: A deep generative model for composite laminate layup design. Composites Science and Technology, 275, 111490. https://doi.org/10.1016/j.compscitech.2025.111490
[2]. Yang, L., Lodh, A., Qiu, J., Castelluccio, G. M., & Zhao, Y*. (2026). Attention-based multi-head feature-fusion network: A generalised method for hot deformation behaviour prediction in low-alloy steels. Engineering Applications of Artificial Intelligence, 165, 113464. https://doi.org/10.1016/j.engappai.2025.113464
[3]. Wang, S., Zhao, Y., Zhang, Z., & Zhao, Y.* (2025). A robust machinery action recognition in construction using a mixed graph convolution block. Expert Systems with Applications, 291, 128540. https://doi.org/10.1016/j.eswa.2025.128540
[4]. Dong, A., Starr, A., & Zhao, Y.* (2025a). An interpretable temporal convolutional framework for Granger causality analysis. IEEE/CAA Journal of Automatica Sinica, 13(3), 665-679. https://doi.org/10.1109/JAS.2025.125396
[5]. Liu, H., Tinsley, L., Deng, K., Wang, Y., Starr, A., Chen, Z., & Zhao, Y.* (2024). A Fiber-Guided Motorized Rotation Laser Scanning Thermography Technique for Impact Damage Crack Inspection in Composites. IEEE Transactions on Industrial Electronics, 71(3), 3163–3172. https://doi.org/10.1109/TIE.2023.3265034.
[6]. Yang, L., Shan, X., Lv, C., Brighton, J., & Zhao, Y.* (2022). Learning Spatio-Temporal Representations With a Dual-Stream 3-D Residual Network for Nondriving Activity Recognition. IEEE Transactions on Industrial Electronics, 69(7), 7405–7414. https://doi.org/10.1109/TIE.2021.3099254.
[7]. Shan, X., Cao, J., Huo, S., Chen, L., Sarrigiannis, P. G., & Zhao, Y.*(2022). Spatial–temporal graph convolutional network for Alzheimer classification based on brain functional connectivity imaging of electroencephalogram. Human Brain Mapping, 43(17), 5194–5209. https://doi.org/10.1002/hbm.25994.
[8]. Zhou, J., Du, W., Yang, L., Deng, K., Addepalli, S., & Zhao, Y.* (2022). Pattern Recognition of Barely Visible Impact Damage in Carbon Composites Using Pulsed Thermography. IEEE Transactions on Industrial Informatics, 18(10), 7252–7261. https://doi.org/10.1109/TII.2021.3134184
[9]. Yang, L., Dong, K., Ding, Y., Brighton, J., Zhan, Z., & Zhao, Y.* (2021). Recognition of visual-related non-driving activities using a dual-camera monitoring system. Pattern Recognition, 116, 107955. https://doi.org/10.1016/j.patcog.2021.107955.
[10]. Du, W., Liu, H., Zhao, Y., Sirikham, A., Addepalli, S., & Zhao, Y.*(2021). A Miniaturized Active Thermography System to Inspect Composite Laminates. IEEE Transactions on Industrial Informatics, 17(5), 3314–3323. https://doi.org/10.1109/TII.2020.3030619.
[11]. Yang, L., Dong, K., Dmitruk, A. J., Brighton, J., & Zhao, Y.* (2020). A Dual-Cameras-Based Driver Gaze Mapping System With an Application on Non-Driving Activities Monitoring. IEEE Transactions on Intelligent Transportation Systems, 21(10), 4318–4327. https://doi.org/10.1109/TITS.2019.2939676.
[12]. Zhao, Y.*, Zhao, Y., Durongbhan, P., Chen, L., Liu, J., Billings, S. A., Zis, P., Unwin, Z. C., De Marco, M., Venneri, A., Blackburn, D. J., & Sarrigiannis, P. G. (2020). Imaging of Nonlinear and Dynamic Functional Brain Connectivity Based on EEG Recordings With the Application on the Diagnosis of Alzheimer’s Disease. IEEE Transactions on Medical Imaging, 39(5), 1571–1581. https://doi.org/10.1109/TMI.2019.2953584.
[13]. Marsot, M., Mei, J., Shan, X., Ye, L., Feng, P., Yan, X., Li, C., & Zhao, Y.* (2020). An adaptive pig face recognition approach using Convolutional Neural Networks. Computers and Electronics in Agriculture, 173, 105386. https://doi.org/10.1016/j.compag.2020.105386.
[14]. Sirikham, A., Zhao, Y.*, Nezhad, H. Y., Du, W., & Roy, R. (2019). Estimation of Damage Thickness in Fiber-Reinforced Composites using Pulsed Thermography. IEEE Transactions on Industrial Informatics, 15(1), 445–453. https://doi.org/10.1109/TII.2018.2878758.
[15]. Zhao, Y.*, Addepalli, S., Sirikham, A., & Roy, R. (2018). A confidence map based damage assessment approach using pulsed thermographic inspection. NDT & E International, 93, 86–97. https://doi.org/10.1016/j.ndteint.2017.10.001.
[16]. Font comas, T., Diao, C., Ding, J., Williams, S., & Zhao, Y.* (2017). A Passive Imaging System for Geometry Measurement for the Plasma Arc Welding Process. IEEE Transactions on Industrial Electronics, 64(9), 7201–7209. https://doi.org/10.1109/TIE.2017.2686349.
[17]. Bai, F., Gagar, D., Foote, P., & Zhao, Y*. (2017). Comparison of alternatives to amplitude thresholding for onset detection of acoustic emission signals. Mechanical Systems and Signal Processing, 84, 717–730. https://doi.org/10.1016/j.ymssp.2016.09.004.
[18]. Zhao, Y.*, Mehnen, J., Sirikham, A., & Roy, R. (2017). A novel defect depth measurement method based on Nonlinear System Identification for pulsed thermographic inspection. Mechanical Systems and Signal Processing, 85, 382–395. https://doi.org/10.1016/j.ymssp.2016.08.033.
[19]. Zhao, Y., Wei, H. L., & Billings, S. A. (2012). A new adaptive fast cellular automaton neighborhood detection and rule identification algorithm. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, 42(4), 1283–1287. https://doi.org/10.1109/TSMCB.2012.2185790.
[20]. Zhao, Y., & Billings, S. A. (2006b). Neighborhood detection using mutual information for the identification of cellular automata. IEEE Transactions on Systems, Man and Cybernetics, Part B (Cybernetics), 36(2), 473–479. https://doi.org/10.1109/TSMCB.2005.859079.
