姓名：郭峰

职称：助理研究员

研究方向：计算机视觉、人工智能在交通基础设施中的交叉研究、图像处理、无损检测等。

个人简介：

郭峰，男，博士（后），永利集团88304官网集团助理研究员。主要从事目标检测、目标追踪、语义分割、实例分割等计算机视觉技术在交通基础设施中的开发应用研究，在Computer-Aided Civil and Infrastructure Engineering、IEEE Transactions on Intelligent Transportation Systems、Automation in Construction、 Advanced Engineering Informatics、Journal of Cleaner Production等国际著名期刊上发表论文20余篇，作为项目骨干完成科研项目10余项，担任IEEE TITS、CBM、JTE Part A、 SHM、IEEE TCSVT等10余个著名期刊审稿人。

教育背景：

2010.09-2014.06，鲁东大学，土木工程学院，土木工程，工学学士

2014.09-2017.06，北京建筑大学，土木工程学院，建筑与土木工程，工程硕士

2018.08-2021.12，美国南卡罗莱纳大学，土木与环境工程学院，土木工程，哲学博士

工作履历：

2017.04-2018.07，香港理工大学，土木与环境工程学院，研究助理

2021.05-2021.08，美国Palo Alto Research Center，Research Intern

2022.01-2022.05，美国南卡罗莱纳大学，土木与环境工程学院，博士后

科研项目：

[1]. Railroad 4.0: intelligent Crossing Assessment and Traffic Sharing System (i-CATSS)，美国联邦铁路局，16万美元，主要参与人。

[2]. Railroad 4.0: intelligent Abnormal Situation Awareness Platform (i-ASAP)，美国联邦铁路局，25.5万美元，主要参与人。

[3]. Railroad 4.0: intelligent Risk Assessment and Prediction System (i-RAPS)，美国联邦铁路局，39.5万美元，主要参与人。

[4]. Autonomous Power-efficient Track Inspection System (APTIS)，美国联邦铁路局，35万美元，主要参与人。

代表性论文：

[1]. Guo, F., Jiang, Z.C., Wang, Y., Chen, C., & Qian, Y. (2022). Dense Traffic Detection at Highway-Railroad Grade Crossings. IEEE Transactions on Intelligent Transportation Systems, 1-14.

[2]. Guo, F., Wang, Y., & Qian, Y. (2022). Computer vision-based approach for smart traffic condition assessment at the railroad grade crossing. Advanced Engineering Informatics, 51, 101456.

[3]. Guo, F., Qian, Y., Wu, Y., Leng, Z., & Yu, H. (2021). Automatic railroad track components inspection using real-time instance segmentation. Computer-Aided Civil and Infrastructure Engineering, 36(3), 362-377.

[4]. Guo, F., Qian, Y., & Shi, Y. (2021). Real-time railroad track components inspection based on the improved YOLOv4 framework. Automation in Construction, 125, 103596.

[5]. Guo, F., & Qian, Y., D. Rizos, & Suo, Z. (2021). Automatic rail surface defects inspection based on Mask R- CNN. Transportation Research Record, 2675(11), 655-668.

[6]. Jiang, Z., Guo, F., Qian, Y., Wang, Y., & Pan, W. D. (2022). A deep learning-assisted mathematical model for decongestion time prediction at railroad grade crossings. Neural Computing and Applications, 34(6), 4715-4732.

[7]. Yu, H., Lin, Y., Yu, J., Dong, N., Jin, J., & Guo, F*. (2022). Recycling potential of used crumb rubber for second-round asphalt modification. Journal of Cleaner Production, 132797.

[8]. Qian, Y., Guo, F.*, Leng, Z., Zhang, Y., & Yu, H. (2020). Simulation of the field aging of asphalt binders in different reclaimed asphalt pavement (RAP) materials in Hong Kong through laboratory tests. Construction and Building Materials, 265, 120651.

[9]. Yu, J., Guo, Y., Peng, L., Guo, F.*, & Yu, H. (2020). Rejuvenating effect of soft bitumen, liquid surfactant, and bio-rejuvenator on artificial aged asphalt. Construction and Building Materials, 254, 119336.

[10]. Zhang, S., Wang, D., Guo, F.*, Deng, Y., Feng, F., Wu, Q., & Li, Y. (2021). Properties investigation of the SBS modified asphalt with a compound warm mix asphalt (WMA) fashion using the chemical additive and foaming procedure. Journal of Cleaner Production, 128789.

联系方式：

地址：永利集团88304官网集团千佛山校区

邮箱：fengg@sdu.edu.cn