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Construction and Operations Management

Yuhan Jiang

Yuhan Jiang

Title

Assistant Professor

Office Building

Solberg Hall

Office

202B

Mailing Address

Solberg Hall 202B
Construction & Operations Management-Box 2223
University Station
Brookings, SD 57007

Biography

Dr. Yuhan Jiang is an Assistant Professor in the Department of Construction and Operations Management at the South Dakota State University. He earned his Ph.D. degree in Civil Engineering from Marquette University. His research focuses on Drone and Artificial Intelligence in Construction Operations, Building and Infrastructural Facility Management. His research results have been published in ASCE Journals of Computing in Civil Engineering, Construction Engineering and Management, Performance of Constructed Facilities, Transportation Engineering, Part B: Pavements, and conference proceedings. His ongoing work of 3D reality data-based building and infrastructure as-built modeling, defect detection and visualization will improve the accuracy and efficiency of facility management in inspection, maintenance, and post-disaster recovery. Dr. Jiang also has extensive experience in community redevelopment planning, and complex systems simulation. His prior research investigated the formation mechanisms of urban villages, and developed a system dynamics model to simulate different redevelopment strategies for sustainable urbanization. 

Dr. Jiang's active projects include:
(1) an aerial and satellite images-based pavement evaluation tool which tracks roadways to collect images for network-level pavement assessment;
(2) a mobile LiDAR-based sidewalk defect detection and mapping method which also provides a web GIS platform for concerned citizens to report sidewalk deficiencies;
(3) a drone photogrammetry-based high-rise building façade modeling method which produces CAD drawings to assist BIM model creation; and,
(4) a novel 3D reconstruction method for determining elevations of large-scale sites which requires much fewer images compared to existing drone photogrammetry.
CM Students do leveling practices on SDSU campus

Teaching

Construction Surveying Lab

A highway segmentation tool based on a deep convolutional neural network (DCNN) is developed to segment the collected highway images into the predefined object categories, where the cracks are identified and labeled in each small-patch of the overlapping assembled label-image prediction.

Research

Pavement Evaluation Tool Using Aerial Imagery and Deep Learning

Education

Ph.D. in Civil Engineering, Marquette University, 2020
M.S. in Construction Management, Guangzhou University, 2015
B.S. in Construction Management, Guangzhou University, 2012

Academic Interests/Expertise

Construction Engineering and Management

Academic Responsibilities

CM 210/210L Construction Surveying/Lab
CM 352 Advanced Cost Estimating with BIM
CM 443 Construction Planning and Scheduling

Professional Memberships

American Society of Civil Engineers (ASCE)
Construction Institute

Area(s) of Research

Drone, Deep learning and Computer Vision
Digital Twin for Construction Sites
Facility Management
Infrastructure Management

Applications of Research

Selected Publications:
1. Jiang, Y., Han, S., and Bai, Y. (2021). “Building and Infrastructure Defect Detection and Visualization Using Drone and Deep Learning Technologies." ASCE Journal of Performance of Constructed Facilities, 35(6), DOI: 10.1061/(ASCE)CF.1943-5509.0001652.
2. Jiang, Y., Han, S., and Bai, Y. (2021). “Development of a Pavement Evaluation Tool Using Aerial Imagery and Deep Learning.” ASCE Journal of Transportation Engineering, Part B: Pavements, 147(3), DOI: 10.1061/JPEODX.0000282.
3. Jiang, Y., and Bai, Y. (2021). “Low–High Orthoimage Pairs-Based 3D Reconstruction for Elevation Determination Using Drone.” ASCE Journal of Construction Engineering and Management, 147(9), DOI: 10.1061/(ASCE)CO.1943-7862.0002067.
4. Jiang, Y., Bai, Y., and Han, S. (2020). “Determining Ground Elevations Covered by Vegetation on Construction Sites Using Drone-Based Orthoimage and Convolutional Neural Network.” ASCE Journal of Computing in Civil Engineering, 34(6), DOI:10.1061/(ASCE)CP.1943-5487.0000930.
5. Jiang, Y., and Bai, Y. (2020). “Estimation of Construction Site Elevations Using Drone-Based Orthoimagery and Deep Learning.” ASCE Journal of Construction Engineering and Management, 146(8), DOI: 10.1061/(ASCE)CO.1943-7862.0001869.

Department(s)

Links

Website