Education
Ph.D., Civil Engineering, Michigan Technological University
M.S., Data Science, University of New Haven
M.S., Construction Management, Syracuse University
Mini MBA, University of Tehran, Iran
B.S., Civil Engineering, Sharif University of Technology, Iran
About Rei
Dr. Reihaneh (Rei) Samsami is the Tagliatela Family Endowed Assistant Professor of Construction Engineering and Management and Coordinator of the M.S. in Construction Engineering and Management program at the University of New Haven. She brings more than 10 years of experience spanning academia, transportation infrastructure, construction technology, and applied artificial intelligence.
Her research focuses on the integration of Artificial Intelligence (AI), computer vision, unmanned aerial systems (UAS), Building Information Modeling (BIM), Digital Twins, and data-driven decision support for infrastructure inspection, construction monitoring, and asset management. She works closely with Departments of Transportation (DOTs), industry partners, and public agencies to develop practical solutions that improve safety, efficiency, and decision-making throughout the project lifecycle.
Dr. Samsami holds a Ph.D. in Civil Engineering from Michigan Technological University, an M.S. in Construction Management from Syracuse University, and an M.S. in Data Science from the University of New Haven. Her interdisciplinary background enables her to bridge engineering expertise with emerging technologies such as machine learning, computer vision, large language models (LLMs), and generative AI.
Prior to joining the University of New Haven, Dr. Samsami conducted transportation research focused on automated construction inspection, UAS-enabled monitoring, thermal imaging, and digital project delivery. Her current work explores AI-assisted infrastructure inspection, explainable AI, vision-language models, digital delivery workflows, and intelligent construction systems.
Dr. Samsami is a licensed Professional Engineer (P.E.), a Certified Associate in Project Management (CAPM), and an active researcher and educator committed to advancing the future of AI-enabled engineering and construction. She serves as a member of the Transportation Research Board (TRB) AKJ11 Construction Section and the American Society of Civil Engineers (ASCE) Data Sensing and Analysis (DSA) Committee. Through her research, teaching, and professional service, she works to bridge emerging technologies and engineering practice to address real-world challenges in transportation and infrastructure systems.
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Selected Publication
Samsami, R., & Kang, S. J. (2026). Lightweight YOLO-Based Detection of Rooftop Thermal Bridges Using Uncrewed Aerial System Thermal Imagery: Comparative Evaluation of Modern YOLO Architectures. ASCE OPEN: Multidisciplinary Journal of Civil Engineering.
Razi, N., Badhan, S. J., & Samsami, R. (2026). Artificial Intelligence (AI) in Construction Management (CM): A Systematic Review of Models and Methods. Buildings.
Badhan, S. J., & Samsami, R. (2025). Artificial Intelligence (AI) in Construction Safety: A Systematic Literature Review. Buildings, 15(22), 4084.
Pokhrel, R., Samsami, R., Elmi, S., & Brooks, C. N. (2024). Automated Concrete Bridge Deck Inspection Using Unmanned Aerial System (UAS)-Collected Data: A Machine Learning Approach. Eng, 5(3), 1937-1960.
Samsami, R. (2024). Optimizing the Utilization of Generative Artificial Intelligence (AI) in the AEC Industry: ChatGPT Prompt Engineering and Design. CivilEng, 5(4), 971-1010.
Samsami, R. (2024). A Systematic Review of Automated Construction Inspection and Progress Monitoring (ACIPM): Applications, Challenges, and Future Directions. CivilEng, 5(1), 265-287.
Samsami, R., Mukherjee, A., & Brooks, C. N. (2021). “Mapping Unmanned Aerial System Data onto Building Information Modeling Parameters for Highway Construction Progress Monitoring.” Transportation Research Record, Journal of the Transportation Research Board of the National Academies, DOI:10.1177/03611981211064277.
Samsami, R., Mukherjee, A., Brooks, C. (2022). “Application of Unmanned Aerial System (UAS) in Highway Construction Progress Monitoring Automation.” Presented at Construction Research Congress 2022 Annual Meeting, March 2022, Washington, D.C. (Ref: AIC-28).
Samsami, R., Mukherjee, A., Brooks, C. (2022). “Application of Unmanned Aerial System (UAS) in Highway Construction Progress Monitoring Automation.” Presented at Transportation Research Board 101st Annual Meeting, January 2022, Washington, D.C. (Ref: TRBAM-22-02980).
Samsami, R., Mukherjee, A. (2021). “Application of Unmanned Aerial Vehicles (UAVs) in Highway Construction Progress Monitoring.” Presented at Transportation Research Board 100th Annual Meeting Transportation Research Board, January 2021, Washington, D.C. (Ref: TRBAM-21-02665).
Minchin, R. E., Samsami, R., Tran, D., D’Angelo, D. A. N., Scott, S., Tian, Y., Russell, J. (2019). “Analysis Of Impediments to A Successful Constructability Process in Highway Construction.” In: Interdependence between Structural Engineering and Construction Management, May 2019, Chicago, IL.
Samsami, R., Minchin, R. E., Tran, D., Tian, Y., Scott, S., D'Angelo, D., Russell, J. (2019). A “Report on the NCHRP 10-99 Project Framework for Implementing Constructability Across the Entire Project Development Process: NEPA to Final Design.” In: Transportation Research Board 98th Annual Meeting, January 2019, Washington, D.C. (19-04686).
Samsami, R., Tavakolan, M. (2016). “A game theoretic model for subcontractors’ partnership in construction: Win-win game.” In: Construction Research Congress 2016, May 2016, San Juan, Puerto Rico. (pp. 597-606).
Samsami, R., Ketabi, A., Gholipour, Y (2016). “Optimal Concession Period in PPP Contract.” In: National Conference of Construction Engineering and Management, June 2016, Tehran, Iran. (Ref: NCCPM02_030).
Research Interests
- Remote Construction Inspection
- Digital Project Delivery and Digital Twins
- Highway Asset Management
- Building Information Modeling
- UAS Data Collection and Analysis
- Automated Progress Monitoring
- Automated QC/QA of Heavy Highway Projects
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