Lingguang Song, Ph.D.
Associate Professor, Construction Management



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Lingguang Song © 2006
University of Houston
Research Interests

The annual construction expenditure of US is more than 600 billion dollars. Although there are still debates about whether the productivity of the construction industry is increasing or declining, the performance of the construction industry is widely perceived as unsatisfactory compared with many other industries. Construction research has great potential to dramatically improve project performance and generate bottom line savings. My research quest concentrates on how to better plan construction process prior to actual construction and how to further improve project control practices and labor productivity during the construction stage. This quest leads me to exciting fields of research in simulation, computer vision, artificial intelligence, and information technologies.




Journal Publications

1. Song, L., Mohamed, Y., and AbouRizk, S. M. (2009) “Early contractor involvement in design and its impact on construction schedule performance.” J. of Manag. in Eng. , ASCE, Vol. 25(1), 12-20. (2009 ASCE Best Paper Award of the Journal of Management in Engineering).

2. Song, L., Liang, D., and Javkhedkar, A. (2008) “Developing lean construction implementation tools: a case study.” J. of Const. Eng. and Manag., ASCE, submitted and under review.

3. Song, L., and AbouRizk, S. M. (2008) “Labor productivity modeling using historical data.” J. of Const. Eng. and Manag. , ASCE, Vol. 20(5), 786-794.

4. Song, L., and AbouRizk, S. M. (2006) “Virtual shop model for experimental planning of steel fabrication projects.” J. of Compu. in Civil Eng. , ASCE. Vol. 20(5), 308-316.

5. Wang, X, Sun, Y., Song, L. , Mei, C. (2008a) “An eco-environmental water demand based model for optimizing water resources using hybrid genetic simulated annealing algorithms. Part I .” To appear in J. of Environ. Eng. in 2009 , Elsevier.
6. Wang, X, Sun, Y., Song, L. , Mei, C. (2008b) “An eco-environmental water demand based model for optimizing water resources using hybrid genetic simulated annealing algorithms. Part II .” To appear in J. of Environ. Eng. in 2009 , Elsevier

7. Wang, X, Yang, L., Sun, Y., Song, L., Zhang, M., and Cao, Y. (2008) “3-D simulation on the water flow field and suspended solids concentration in the rectangular sedimentation tank.” J. of Environ. Eng. , ASCE, Vol. 134(11), 902-911.

8. Song, L., Wang, P., and AbouRizk, S. M. (2006) “Virtual shop modeling system for industrial fabrication projects.” J. of Simulation Theory and Practice , EUROSIM, Vol. 14(2), 649-662.

9. Zhong, D., Li, M., Song, L., and Wang, G. (2006) “Enhanced NURBS modeling and visualization for large 3D geoengineering applications: An example from the Jinping first-level hydropower engineering project, China.” Computers & Geosciences . Science Direct, Vol. 32, 1270-1282.

10. Song, L., AL-Battaineh, H., and AbouRizk, S. M. (2005) “Modeling uncertainty with an integrated construction simulation system.” Canadian J. of Civil Eng ., CSCE, Vol. 32(3), 533-542.

11. Song, L., and AbouRizk, S. M. (2004) “Quantifying engineering project scope for productivity modeling.” J. of Const. Eng. and Manag., ASCE, Vol. 131(3), 360-367.

12. Zhong, D., Li, J., Zhu, H., and Song, L. (2004) “GIS-based visual simulation methodology for concrete dam construction process.” J. of Const. Eng. and Manag., ASCE, Vol. 130(5), 742-750.

13. Zhong, D., and Song, L. (1999) “Visual resource-oriented construction simulation.” J. of Tianjin University , Vol. 6, 682-686.

14. Zhong, D., Huang, L., Mi, Z., and Song, L. (1998) “Predicting water intake volume during the flood season using neural networks.” Chinese J. of Manag. Sciences , Vol. 3, 45-50.

Conference papers

15. Song, L., and Lee, S. (2009) “Incorporating virtual field information in learning construction operations.” To appear in 2009 ASEE Annual Conference , Austin , TX.
16. Rachmat, F. H., Song, L., and Lee, S. (2009) “Applying stochastic linear scheduling method to pipeline construction.” To appear in 3rd International Conf. on Const. Eng. & Manag., Jeju, Korea.

17. Ghatala, M., Lee, S., and Song, L. (2009) “A simulation approach to construction management education.” To appear in 2009 ASEE Annual Conference, Austin, TX.

18. Song, L., Cooper, C., and Lee, S. (2009) “Real-time simulation for look-ahead scheduling of heavy construction projects.” To appear in Proc. 2009 Const. Research Congress . ASCE, Seattle , WA .

19. Song, L., Ramos, F., and Arnold, K. (2008) “A framework for real-time simulation of heavy construction operations.” To appear in Proc. 2008 Winter Simulation Conference , Miami , FL.

20. Song, L., Liang, D., and Javkhedkar, A. (2008) “A case study on applying lean construction to concrete construction projects.” Proc. 44th ASC International Conf. ASC. Auburn , AL .

21. Liang, D., and Song L. (2008) “Development of a task-based safety model for construction projects.” Proc. W99 CIB Conference 2008 , CIB, Gainesville , FL.

22. Lee, S., Spencer, H., Song, L. , and Kim, K. (2008) “Development of a front end planning tool for sustainability.” Submitted to 2009 ICCEM/ICCPM , Jeju, Korea.

23. Lee, S., Fuzetti, C., Song, L. , and Kim, K. (2008) “Using process mapping in construction process to reduce change orders.” Submitted to 2009 ICCEM/ICCPM , Jeju, Korea.
24. Song, L. (2007) “Progress measurement using CAD-based vision system.” Proc. of the 2007 Construction Research Congress. ASCE, Freeport , Bahamas .
25. Song, L., Mohamed, Y., and AbouRizk, S. M. (2006) “Contractor's early involvement in design.” Proc. 2006 AACE International Transaction , AACE, Las Vegas , NV .
26. Song, L., and AbouRizk, S. M. (2006) “Modeling labor productivity in steel fabrication.” Proc. 2006 AACE International Transaction . AACE, Las Vegas , NV .
27. Song, L., and AbouRizk, S. M. (2003) “Building a virtual shop model for steel fabrication.” Proc. 2003 Winter Simulation Conference. ACM/SIGSIM, New Orleans , LA.
28. Song, L., Allouche, M., and AbouRizk, S. M. (2003) “Measuring and estimating steel drafting productivity.” Proc. 2003 Construction Research Congress . ASCE, Honolulu , HI .


1. Song, L., Zhang, X. and Ruwanpura, J. (2008). “A goal and cross-industry perspective on EVM practice and future trends.” Project Management Institute (PMI). 5/2008-4/2009.
2. Barbieri, E., Lee, S., and Song, L. (2007) “Center for Technology Literacy: An upward mobility strategy for economic growth.” Economic Development Administration, US Dept. of Commerce. 7/2007-6/2010.

3. Song, L. (2007) “Implementing a CAD-based vision system for progress measurement.” Fluor Partner Grant, Fluor Corporation. 9/2007-8/2008.

4. Song, L. (2006) “Implementing and measuring lean application in concrete construction.” 2006 Baker Concrete Research Program, Baker Concrete Inc., 5/2006-12/2006.

5. Song, L. (2006) “Construction Management Laboratory: Automated project progress measurement using CAD-based vision system.” Fluor Partner Grant , Fluor Corporation. 9/2006-8/2007. PI.

6. Song, L. (2006) “Mapping project execution process at Gulf States Inc.” Gulf States Inc. , Freeport, TX. 9/2006-12/2006. PI and Faculty advisor.

7. Lee, S. and Song, L. (2005) “A virtual construction environment for construction management learning”, FDIP Program B, University of Houston, 5/2005-5/2006.

8. Song, L. (2005) “Development of a web-based construction operation simulation environment”, FDIP Program A, University of Houston, 5/2005-5/2006.

9. Song, L. (2004) “Contractor's early involvement in industrial construction projects”, New Faculty Grant, University of Houston, 2/2005 to 8/2005.

10. Song, L. (2004) “Incorporating model uncertainty in risk analysis”, Small Grant, University of Houston, 12/2004-8/2005.

11. Song, L. (2004) “A learning EPC project modeling framework for industrial construction.” HEAF Startup Grant, University of Houston.

Active Projects

Real-time Construction Simulation

Successful construction project execution and control relies on an efficient job site data acquisition system that collects and analyzes time, cost, and safety performance data. The current practice of job site data collection and analysis is based on visual inspection and manual analysis which is time-consuming and costly. Collected data and derived decisions many times come too late to avoid schedule delay, cost overrun, or a safety accident. This research proposes a real-time construction site simulator based on such technologies, including computer vision, location tracking, and simulation. The project gains supports from HCSS and Gilchrist Construction.


Earned Value Management System (EVMS)

Earned Value Management (EVM) provides an integrated control methodology that combines the measurement of technical performance, schedule performance, cost performance and provides early warnings of performance problems for timely corrective actions. In recent years, the ever increasing level of globalization and cross-industry collaboration in a project environment generates a great need for a clear understanding of EVM practice and standards across geographic and industry boundaries. The long term goal of this research is to characterize industry needs and identify best practices and standards of EVM to improve overall project planning and control practice. The objective of this project is to understand the current practice and future trend of EVM usage, standards, and services across different industry sectors and geographic regions. The project is funded by PMI.


If you are interested

in the EVM survey,

Click here.

Computer vision & project progress monitoring

Accurately and timely monitoring and control project progress is critical to project success. This research presents a conceptual framework for progress measurement using field images acquired by a digital camera. It uses a model-based vision approach that integrates computer vision techniques and CAD. A number of image processing and vision techniques are used to recognize and measure image objects and compare them against their counterparts in the CAD models. This comparison can generate progress measurement information for project control purposes.
The research team is currently working on software development and developing realistic business cases for further deployment. Pasadena Refining System Inc. (PRSI) and Fluor Corporation kindly provide access to an industrial project, S Zorb project in Pasadena, TX, for data collection and system testing. Current project result was presented in 2007 ASCE CRC conference.

Only avaiable for IE 6 or above

Vertical scheduling integration & Lean Construction

This research studies lean construction concepts and its application at both project and operation levels. In conjunction with a concrete contractor, actual construction projects were observed and problem areas contributing to delay and other wastes were identified. At the project level, lack of coordination among contractors was cited as one of the major factors contributing to project delays. This research proposes integration of the Last Planner concept and Linear Scheduling Method to improve communication among project participants for short-interval scheduling. Related software is developed for implementing this scheduling tool. At the operation level, a systematic approach of waste identification, operation re-design, and employee training is applied to eliminate wastes in the field operation. A 3D animation training program is created for employee training. This project is funded by Baker Concrete.


Contact Information

Lingguang Song, Ph.D
Associate Professor
Construction Management
T2 375 T2
University of Houston
Houston TX 77204
Tel: 713-743-4377
Fax: 713-743-4032


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