2003年6月获工学博士学位；2006年7月晋升副教授，2014-2015年澳大利亚墨尔本大学访问学者。主要研究方向为智能交通系统目标检测和防碰撞、基于深度学习的气动建模和网络流量异常感知。

中国计算机学会互联网专委会委员、四川省海外高层次留学人才、四川省科技厅科技项目评审专家、担任多个国际学术会议程序委员会委员、国际国内重要学术期刊审稿人。 

主持国家自然科学基金原创探索项目、国家数值风洞工程一期项目、科技部科技支撑计划项目、国家发改委CNGI项目、四川省省级战略性新兴产业发展促进资金项目等多项重要科研项目，参与863计划等多项国家项目。

在IEEE IoT Journal、IEEE TAES、IEEE TITS、IEEE TVT、IET Communications、JNCA、Computer Networks、ITSC、ACM/IEEE ANCS、电子学报、空气动力学报等国内外重要学术刊物和国际会议发表论文40余篇。

近年来发表的部分论文：

2024:

Fang, S., Xiang, Y., Zhang, J., Wang, W. (2025). A Novel Geometric-Encoded and Feature-Fused Model for Pressure Distribution Prediction on Airfoils. In PRICAI 2024: Trends in Artificial Intelligence. PRICAI 2024. Lecture Notes in Computer Science(), vol 15283. Springer, Singapore. https://doi.org/10.1007/978-981-96-0122-6_13  (通信作者）

Xiaorui Bai, Wenyong Wang, Jun Zhang, Yueqing Wang, Yu Xiang, Novel deep learning methods for 3D flow field segmentation and classification, Expert Systems with Applications, Volume 251, 2024, 124080,

https://doi.org/10.1016/j.eswa.2024.124080. (通信作者）

2023：

H. Li, Y. Xiang, H. Xu and W. Wang, "Pedestrian Recognition with Radar Data-Enhanced Deep Learning Approach Based on Micro-Doppler Signatures," 2023 IEEE 35th International Conference on Tools with Artificial Intelligence (ICTAI), Atlanta, GA, USA, 2023, pp. 437-443, doi: 10.1109/ICTAI59109.2023.00070. （通信作者）

Y. Xiang, L. Hu, G. Zhang, J. Zhang and W. Wang, "A Manifold-Based Airfoil Geometric-Feature Extraction and Discrepant Data Fusion Learning Method," in IEEE Transactions on Aerospace and Electronic Systems, vol. 59, no. 5, pp. 6555-6569, Oct. 2023, doi: 10.1109/TAES.2023.3276735. 

Bai, X., Wang, W., Zhang, J., Wang, Y., & Xiang, Y. (2023). Novel deep learning methods for 3D flow field segmentation and classification. arXiv preprint arXiv:2305.11884.

2022：

Y. Xiang, Y. Huang, H. Xu, G. Zhang and W. Wang, "A Multi-Characteristic Learning Method with Micro-Doppler Signatures for Pedestrian Identification," 2022 IEEE 25th International Conference on Intelligent Transportation Systems (ITSC), 2022, pp. 3794-3799, doi: 10.1109/ITSC55140.2022.9922125

L. Hu, W. Wang, Y. Xiang and J. Zhang, "Flow Field Reconstructions with GANs based on Radial Basis Functions," in IEEE Transactions on Aerospace and Electronic Systems, doi: 10.1109/TAES.2022.3152706.

Liwei Hu, Yu Xiang, Jun Zhang, Zifang Shi, Wenzheng Wang, Aerodynamic data predictions based on multi-task learning, Applied Soft Computing,Volume 116, 2022, 108369, https://doi.org/10.1016/j.asoc.2021.108369. （通信作者）

2021：

张骏，张广博，程艳青，胡力卫，向渝，汪文勇，“一种气动大差异性数据多任务学习方法”，空气动力学学报，2021, 39(s): 1-10.

J. Fang, Y. Xiang, Y. Huang, Y. Cui and W. Wang, "A Vehicle Control Model to Alleviate Traffic Instability," in IEEE Transactions on Vehicular Technology,  2021, 70(10), pp. 9863–9876 doi: 10.1109/TVT.2021.3109800. （通信作者）

L.Huang, J.Ran, W.Wang, T.Yang and Y.Xiang, A Multi-channel Anomaly Detection Method with Feature Selection and Multi-scale analysis. Computer Networks，Volume 185,2021,107645, doi:10.1016/j.comnet.2020.107645. (通信作者）

2020:

Hu L, Xiang Y, Zhan J, et al. Aerodynamic Data Predictions Based on Multi-task Learning[J]. arXiv preprint arXiv:2010.09475, 2020.

Hu L, Wang W, Xiang Y, et al. Flow Field Reconstructions with GANs based on Radial Basis Functions[J]. arXiv preprint arXiv:2009.02285, 2020.

Hu L, Zhang J, Xiang Y, et al. Neural Networks-Based Aerodynamic Data Modeling: A Comprehensive Review[J]. IEEE Access, 2020, 8: 90805-90823.

Y. Xiang, S. Huang, M. Li, J. Li and W. Wang, "Rear-End Collision Avoidance-Based on Multi-Channel Detection," in IEEE Transactions on Intelligent Transportation Systems, vol. 21, no. 8, pp. 3525-3535, Aug. 2020, doi: 10.1109/TITS.2019.2930731.

2019:

Xiang Y, Ran J, Huang L, et al. A Traffic Anomaly Detection Method based on Multi-Scale Decomposition and Multi-Channel Detector[C]//2019 ACM/IEEE Symposium on Architectures for Networking and Communications Systems (ANCS). IEEE, Sept. 2019: 1-6. DOI: 10.1109/ANCS.2019.8901897

J. Li, Y. Xiang, J. Fang, W. Wang and Y. Pi, "Research on Multiple Sensors Vehicle Detection with EMD-Based Denoising," in IEEE Internet of Things Journal, vol. 6, no. 4, pp. 6262-6270, Aug. 2019.   DOI: 10.1109/JIOT.2018.2890541 (通信作者)

2018:

Xiang Y, Gou L, He L, et al. A SVR–ANN combined model based on ensemble EMD for rainfall prediction[J]. Applied Soft Computing, 2018, 73: 874-883.

2016:

Xiang Y, Wang X, He L, Wang W, Moran W (2016) Spatial-Temporal Analysis of Environmental Data of North Beijing District Using Hilbert-Huang Transform. PLOS ONE 11(12): e0167662. doi: 10.1371/journal.pone.0167662

Xiang Y, Xuan Z, Tang M, et al. 3D space detection and coverage of wireless sensor network based on spatial correlation [J]. Journal of Network and Computer Applications, 2016, 61: 93-101.

1991.9 -- 1995.7
电子科技大学       电子工程       大学本科毕业       工学学士学位

1995.9 -- 1998.3
电子科技大学       通信与信息系统       硕士研究生毕业       工学硕士学位

1998.9 -- 2003.6
电子科技大学       通信与信息系统       博士研究生毕业       工学博士学位

2008.7 -- 至今

电子科技大学计算机科学与工程学院      副教授

2003.7 -- 2008.6

电子科技大学信息中心      副教授