王 骞


通讯方式:

研究方向:

办公地点:

 

 

个人简介

王骞,东南大学青年首席教授、博导,入选国家海外高层次人才计划青年项目。主要研究方向包括智能建造与运维、机器视觉、建筑机器人、质量与病害检测、语义模型重建等。在Automation in Construction, Computer-Aided Civil and Infrastructure Engineering, ASCE Journal of Computing in Civil Engineering, Advanced Engineering Informatics等国际权威期刊发表SCI/SSCI论文50余篇。谷歌学术累计被引用3300余次,H指数29,入选ESI高被引论文3篇,授权国际、国内发明专利7项。2022-2023连续入选斯坦福大学全球前2%科学家榜单(年度影响力榜单)。兼任中国图学学会BIM专业委员会委员、Journal of Intelligent Construction期刊青年编委、Smart Construction期刊青年编委、Buildings期刊编委等职务。

曾在知乎创作内容百余篇,累计获赞15000+,然最近极少更新。希望论文被引用数早日追上知乎获赞数。


教育背景

2009-2013,本科,清华大学,工程管理专业

2013-2017,博士,香港科技大学,土木工程专业(双博士学位项目)

2013-2017,博士,韩国科学技术院,土木与环境工程专业(双博士学位项目)

 

工作经历

2017-2022,新加坡国立大学建筑环境系,助理教授

2022-至今,东南大学土木工程学院,教授


招生方向:

学术硕士:土木工程(土木工程建造与管理)

专业硕士:土木水利

博士:土木工程(土木工程建造与管理)


招生名额:

每年招收硕士研究生3名,博士研究生2名(包括本科直博,欢迎对科研有热情的本科生申请!)

欢迎对智能建造与运维、机器视觉等领域感兴趣的同学申请硕、博研究生,以及博士后岗位

有意申请者,请联系我的微信(19720250801)或邮箱(qianwang@seu.edu.cn)


I am also accepting outstanding foreign students supported by CSC scholarship. If you are taking a Master program in reputable Chinese universities (such as 211/985) and applying for PhD program at Southeast University, you are welcome to contact me. I don't have time to reply your email if you cannot pass my initial screening. Sorry!


学术兼职

担任中国图学学会BIM专业委员会委员

担任SCI期刊Buildings编委

担任Journal of Intelligent Construction期刊青年编委

担任Smart Construction期刊青年编委

担任比利时自然科学基金外审专家

担任ISO 16739-1标准工作组成员

担任ISO TC 59 SC 13标准审查委员会成员

担任第八届建造工程与项目管理国际会议技术委员会分会主席

担任第十六届虚拟现实建造工程应用国际会议大会秘书、组委会成员

担任第二十八届建设管理与房地产发展国际学术研讨会组委会成员

教学课程

工程项目管理II(B)

领导力素养II(研讨)(工管)

专业写作(工管)

科研、教改项目

国家重点研发计划课题,建筑工程施工质量全过程贯通式精益管理与评价研究,主持,2023-2027

江苏省社科基金青年项目,江苏生命线适灾韧性评估与提升研究,参与,2024-2025

国家自然科学基金面上项目,设计驱动视域下城市地铁系统的韧性收益研究:形成机理、动态测度及智能优化,参与,2024-2027

中央高校优秀青年团队,参与,2023-2025

东南大学科研启动经费,主持,2023-2026

国家级海外高层次人才计划青年项目,主持,2022-2025

Integrated Robotic-BIM Inspection System, National Robotics Programme (NRP) – Robotics Domain Specific (RDS), 新加坡科技研究局,参加

Integrated Smart Predictive Remote Sensing Technology for Ground Settlement Monitoring, Cities of Tomorrow (CoT) R&D Programme, 新加坡国家科研基金会,主持

Artificial Intelligence Assisted Scan-to-BIM for Existing Buildings in A&A Projects, 新加坡教育局,主持

Automated Geometry Quality Inspection of PPVC/PBU Using Point Cloud Data and BIM, 新加坡教育局,主持


论文和专著

发表论文:

ResearchGate:https://www.researchgate.net/profile/Qian-Wang-119

Google Scholar: https://scholar.google.com/citations?user=pd2EAqgAAAAJ&hl=en


研究方向一:基于点云的结构尺寸质量检查

1.       Tang, X., Wang, M., Wang, Q.*, Guo, J., and Zhang, J., 2022. Benefits of terrestrial laser scanning for construction QA/QC: a time and cost analysis. Journal of Management in Engineering, 38(2), 05022001.

2.       Tan, Y., Li, S., and Wang, Q.*, 2020. Automated geometric quality inspection of prefabricated housing units using BIM and LiDAR.Remote Sensing, 12(15), 2492.

3.       Guo, J., Wang, Q.*, and Park, J.H., 2020. Geometric quality inspection of prefabricated MEP modules with 3D laser scanning. Automation in Construction, 111, 103053.

4.       Wang, Q., Sohn, H., and Cheng, J.C.P.*, 2019. Development of high-accuracy edge line estimation algorithms using terrestrial laser scanning. Automation in Construction, 101, 59-71.

5.       Kim, M.K., Wang, Q.*, and Li, H., 2019. Non-contact sensing based geometric quality assessment of buildings and civil structures: a review. Automation in Construction, 100, 163-179.

6.       Guo, J., Yuan, L., and Wang, Q.*, 2020. Time and cost analysis of geometric quality assessment of structural columns based on 3D terrestrial laser scanning. Automation in Construction, 110, 103014.

7.       Wang, Q.*, 2019. Automatic checks from 3D point cloud data for safety regulation compliance for scaffold work platforms. Automation in Construction, 104, 38-51.

8.       Wang, Q., Sohn, H.*, and Cheng, J.C.P., 2016. Development of a mixed pixel filter for improved dimension estimation using AMCW laser scanner. ISPRS Journal of Photogrammetry and Remote Sensing, 119, 246-258.

9.       Wang, Q., Kim, M.K., Cheng, J.C.P., and Sohn, H.*, 2016. Automated quality assessment of precast concrete elements with geometry irregularities using terrestrial laser scanning. Automation in Construction68, 170-182.

10.   Wang, Q., Cheng, J.C.P.*, and Sohn, H., 2017. Automated estimation of reinforced precast concrete rebar positions using colored laser scan data. Computer-Aided Civil and Infrastructure Engineering, 32(9), 787–802.

 



研究方向二:基于点云的三维模型重建

1.       Wang, Q.*, Li, J.*, Tang, X., and Zhang, X., 2022. How data quality affects model quality in scan-to-BIM: A case study of MEP scenes. Automation in Construction, 144, 104598.

2.       Wang, B., Wang, Q.*, Cheng, J.C.P.*, and Yin, C., 2022. Object verification based on deep learning point feature comparison for scan-to-BIM. Automation in Construction, 142, 104515.

3.       Qiu, Q., Wang, M., Guo, J., Liu, Z., and Wang, Q.*, 2022. An adaptive down-sampling method of laser scan data for scan-to-BIM. Automation in Construction, 135, 104135.

4.       Wang, B., Wang, Q.*, Cheng, J.C.P.*, Song, C., and Yin, C., 2022. Vision-assisted BIM reconstruction from 3D LiDAR point clouds for MEP scenes. Automation in Construction, 133, 103997.

5.       Wang, B., Yin, C., Luo, H., Cheng, J.C.P.*, and Wang, Q.*, 2021.Fully automated generation of parametric BIM for MEP scenes based on terrestrial laser scanning data. Automation in Construction, 125, 103615.

6.       Qiu, Q., Wang, M., Tang, X., and Wang, Q.*, 2021. Scan planning for existing buildings without BIM based on user-defined data quality requirements and genetic algorithm. Automation in Construction, 130, 103841.

7.       Yang, L., Cheng, J.C.P.*, and Wang, Q.*, 2020. Semi-automated generation of parametric BIM for steel structures based on terrestrial laser scanning data. Automation in Construction, 112, 103037.

8.       Yuan, L., Guo, J., and Wang, Q.*, 2020. Automatic classification of common building materials from 3D terrestrial laser scan data. Automation in Construction, 110, 103017.

9.       Wang, Q.*, Guo, J., and Kim, M.K., 2019.An application oriented scan-to-BIM framework. Remote Sensing, 11(3), 365.

10.   Wang, Q., Sohn, H.*, and Cheng, J.C.P., 2018. Automatic as-built BIM creation of precast concrete bridge deck panels using laser scan data. Journal of Computing in Civil Engineering32(3), 04018011.

11.   Wang, Q., Tan, Y.*, and Mei, Z., 2020. Computational methods of acquisition and processing of 3D point cloud data for construction applications. Archives of Computational Methods in Engineering, 27(2), 479-499. (ESI highly cited paper as of September/October 2020)

12.   Wang, Q.*, and Kim, M.K., 2019. Applications of 3D point cloud data in the construction industry: a fifteen-year review from 2004 to 2018. Advanced Engineering Informatics, 39, 306-319. (Most cited articles from Advanced Engineering Informatics as of January 2022; ESI highly cited paper as of January/February 2022)

 



研究方向三:基于图像的建筑病害检测

1.       Guo, J., Wang, Q.*, Su, S., and Li, Y., 2023.Informativeness-guided active learning for deep learning–based façade defects detection. Computer-Aided Civil and Infrastructure Engineering.

2.       Cui, Z., Wang, Q.*, Guo, J., and Lu, N.*, 2022. Few-shot classification of façade defects based on extensible classifier and contrastive learning. Automation in Construction, 141, 104381.

3.       Li, J., Wang, Q.*, Ma, J., and Guo, J., 2022. Multi-defect segmentation from façade images using balanced copy-paste method. Computer-Aided Civil and Infrastructure Engineering, 37(11), 1434-1449.

4.       Guo, J., and Wang, Q.*, 2022. Human-related uncertainty analysis for automation-enabled façade visual inspection: a Delphi study. Journal of Management in Engineering,38(2), 04021088.

5.       Guo, J., Wang, Q.*, and Li, Y., 2021. Evaluation-oriented façade defects detection using rule-based deep learning method. Automation in Construction,131, 103910.

6.       Guo, J., Wang, Q.*, and Li, Y., 2021.Semi-supervised learning based on convolutional neural network and uncertainty filter for façade defects classification. Computer-Aided Civil and Infrastructure Engineering,36(3), 302-317.

7.       Guo, J., Wang, Q.*, Li, Y., and Liu, P., 2020. Façade defects classification from imbalanced dataset using meta learning-based convolutional neural network. Computer-Aided Civil and Infrastructure Engineering, 35(12), 1403-1418.

 



研究方向四:BIM与数字孪生

1.       Zhou, X., Sun, K., Wang, Q.*, Wang, J., Huang, X., and Zhou, W., 2023. IEDW: A BIM-based indoor electric distribution wiring algorithm using graph theory and capacity-limited multiple traveling salesman problem solver. Advanced Engineering Informatics, 56, 101999.

2.       Zhou, X., Wang, M., Liu, Y.*, Wang, Q.*, Guo, M.*, and Zhao, J., 2021. Heterogeneous network modeling and segmentation of building information modeling data for parallel triangulation and visualization. Automation in Construction, 131, 103897.

3.       Su, S., Li, S., Ju, J., Wang, Q.*, and Xu, Z., 2021. A building information modeling-based system for estimating building demolition waste and evaluating its environmental impacts. Waste Management, 134, 159-169.

4.       Su, S.*, Wang, Q., Han, L., Hong, J., and Liu, Z., 2020. BIM-DLCA: An integrated dynamic environmental impacts assessment model for buildings. Building and Environment, 183, 107218.

5.       Chen, K., Chen, W., Cheng, J.C.P.*, and Wang, Q., 2020. Developing efficient mechanisms for BIM-to-AR/VR data transfer. Journal of Computing in Civil Engineering, 34(5), 04020037.

6.       Cheng, J.C.P., Chen, W.*, Chen, K., and Wang, Q., 2020. Data-driven predictive maintenance planning framework for MEP components based on BIM and IoT using machine learning algorithms. Automation in Construction, 112, 103087. (ESI highly cited paper as of January/February 2022)

7.       Chen, W., Chen, K., Cheng, J.C.P.*, Wang, Q., and Gan, V.J., 2018. BIM-based framework for automatic scheduling of facility maintenance work orders. Automation in Construction, 91, 15-30.


专利、软件著作权

1.       Sohn, H., Wang, Q. and Yoon, S. 3-dimensional laser scanner, KR Patent (No. 10-1840328), 2018-03-14.

2.       Sohn, H., and Wang, Q. Method for detecting position of rebar in reinforced precast concrete and detecting apparatus the same, KR Patent (No. 10-1932227), 2018-12-18.

3.       Sohn, H., and Wang, Q. Method for detecting reinforcing rebar position in precast concrete and apparatus for detecting same, PCT International Patent (No. WO2018190570A1), 2018-10-18.

4.       Sohn, H., Wang, Q. and Kim, M.K. Mirror based automated dimensional inspection of side shape of precast concrete elements using 3D laser scanner, KR Patent (No.  10-1651058), 2016-08-19.

5.       孙勋,王骞,金珉玖. 预制混凝土质控装置、质控系统及装置操作方法,国家发明专利,(ZL 2016 1 0099315.5),2018-10-23.

6.       Sohn, H., Yoon, S. and Wang, Q. Method for estimating position of precast components and position estimation device, PCT International Patent (No. WO2018212472A1), 2018-11-22.

7.       Sohn, H., Yoon, S. and Wang, Q. Method of estimating placement of precast components and placement estimating device, KR Patent (No. 10-1905103), 2018-09-28.

1.       Sohn, H., and Wang, Q. METHOD FOR DETECTING POSITION OF REBAR OF PRECAST CONCRETE AND DETECTING APPARATUS THEREOF, KR Patent (Publication No. KR1020180114316), 18 December 2018.

2.       Sohn, H., Yoon, S. and Wang, Q. METHOD AND DEVICE FOR ESTIMATING POSITION OF PRECAST COMPONENTS, KR Patent (Publication No. KR1019051030000), 28 November 2018.

3.       Sohn, H., Yoon, S. and Wang, Q. METHOD FOR ESTIMATING POSITION OF PRECAST COMPONENTS AND POSITION ESTIMATION DEVICE, WIPO Patent (Publication No. WO2018212472), 22 November 2018.

4.       Sohn, H., Wang, Q. and Kim, M.K. PRECAST CONCRETE QUALITY CONTROL DEVICE AND PRECAST CONCRETE QUALITY CONTROL SYSTEM INCLUDING THE SAME, CN Patent (Publication No. CN105910551), 23 October 2018.

5.       Sohn, H., and Wang, Q. METHOD FOR DETECTING REINFORCING REBAR POSITION IN PRECAST CONCRETE AND APPARATUS FOR DETECTING SAME, WIPO Patent (Publication No. WO2018190570), 18 October 2018.

6.       Sohn, H., Wang, Q. and Yoon, S. THREE-DIMENSIONAL LASER SCANNER, KR Patent (Publication No.  KR1018403280000), 20 March 2018.

7.       Sohn, H., Wang, Q. and Kim, M.K. PRECAST CONCRETE SHAPE MANAGEMENT DEVICE AND PRECAST CONCRETE SHAPE MANAGEMENT SYSTEM INCLUDING SAME, KR Patent (Publication No.  KR1016510580000), 25 August 2016.


荣誉和奖励

入选国家级海外高层次人才计划青年项目

入选斯坦福大学全球前2%科学家榜单(年度影响力榜单)(2022-2023

第四届全国BIM学术会议优秀论文奖

2023年东南大学土木工程学院年度特别奉献奖

Automation in Construction优秀审稿人

Journal of Cleaner Production优秀审稿人

指导博士生获得国家优秀自费留学生奖学金

指导本科生获得新加坡国立大学颁发的NUS-JTC i3创新奖章


指导学生

硕士研究生:

2023:赵鸿翔 聂祥 杨周洲

2024:赵敏如 李泽宇


博士研究生:

2024:越宏哲