Construction Analytics

Chapter 1. Introduction to Construction Analytics.- Chapter 2. Construction Forecasting using Univariate Time Series Models.- Chapter 3. Construction Forecasting Using Time-series Volatility Models.- Chapter 4. Construction Forecasting using Multivariate Time Series Models.- Chapter 5. Construction Forecasting Using Recurrent Neural Networks.- Chapter 6. Investment Valuation of Construction Projects Under Uncertainty.- Appendices: Construction time series datasets, including National Highway Construction Cost Index (NHCCI), Federal Highway Construction Spending, Iowa Highway Construction.

Dr. Mohsen Shahandashti is an associate professor in the Department of Civil Engineering at the University of Texas at Arlington (UTA). He joined UTA immediately after receiving Ph.D. from the Georgia Institute of Technology. He is a licensed Professional Engineer (PE) in Civil Engineering in Texas. He has published 49 peer-reviewed journal articles in the leading infrastructure and construction journals and has received several awards, including the 2019 AASHTO High-Value Research "Sweet Sixteen" Award for leading the TxDOT Research Project "Exploring Rapid Repair Methods for Embankment Slope Failure" and the best paper award in the category of Optimization and Computational Techniques from the International Associations for Automation and Robotics in Construction.


Dr. Bahram Abediniangerabi is a senior data scientist working in the banking industry. He obtained his Ph.D. in Civil Engineering with a focus on Construction Data Analytics from the University of Texas at Arlington in 2019. He is involved in several research projects related to time series forecasting, natural language processing, and machine learning applications in construction. His interest is mainly focused on open-source projects related to Conversational AI, social media analytics, and quantitative finance. He has published several research papers in various areas, such as construction time series forecasting, investment valuation under uncertainty, and building energy use prediction.


Dr. Ehsan Zahed Ph.D., P.E. is a multidisciplinary professional engineer with demonstrated experience in Civil Engineering practice, research, and education. He obtained a B.Sc. degree in Water Science and Technology and an M.Sc. degree in Hydraulic Structures focusing on river engineering and the hydraulic design of channels, dams, and bridges, and then received his master's and Ph.D. degrees in Construction Engineering and Management from the University of Texas at Arlington. Dr. Zahed