Yunjeong (Leah) Mo

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Bio

Dr. Mo is an assistant professor in the Department of Civil, Construction and Environmental Engineering. Dr. Mo’s core research area comprises Humans in Built Environments focusing on Energy and Occupant Behavior, AEC Work Process Automation, Construction Safety, and Diverse Occupants. Her core research areas have expanded to Digital Twin-Based Building Management Systems, and Emerging Technologies for AEC Courses by incorporating Machine Learning (ML), Natural Language Processing (NLP), Building Information Modeling (BIM), Virtual Reality (VR), Augmented Reality (AR), etc. Before joining Iowa State University, Dr. Mo worked as an assistant professor at University of North Florida. Dr. Mo also has industry work experience as a system analyst and programmer at LG CNS in Seoul, Korea. Dr. Mo is a LEED AP BD+C (Building Design and Construction).

Education

• Ph.D. Construction Management, Michigan State University, 2018
• M.S. Building Performance and Diagnostics, Carnegie Mellon University, 2016
• M.S. Construction Management, Michigan State University, 2012
• B.S. Housing and Interior Architecture, Yonsei University (Seoul, Korea), 2002

Research Interests

• Smart Building Energy Management and Occupant Behavior
• Sustainable Built Environment
• Smart City and Infrastructure
• BIM, VR/AR, Digital Twin
• Data Analytics and Machine Learning
• Construction Work Process Automation

Publications

For a full list of publications, please visit her Google Scholar page.

Selected Publications

Mo, Y. & Zhao, D. (2022). Spatial Analysis on Routine Occupant Behavior Patterns and Associated Factors in Residential Buildings, Construction Research Congress (CRC) 2022 in Arlington, VA, March 9-12, 2022.

Mo, Y. & Zhao, D. (2021). Effective Factors for Residential Building Energy Modeling using Feature Engineering. Journal of Building Engineering, 102891.

Mo, Y. & Zhao, D. (2021). Application of Occupant Behavior Prediction Model on Residential Big Data Analysis, In Proceedings of The 8th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation (BuildSys), in Coimbra, Portugal, November 17-18, 2021.

Mo, Y., Zhao, D., Du, J., Syal, M., Aziz, A., & Li, H. (2020). Automated staff assignment for building maintenance using natural language processing. Automation in Construction, 113, 103150.

Mo, Y., Dhara, A., Liu, W., & Zhao, D. (2018). Data-driven Approach to Scenario Determination for VR-based Construction Safety Training. In Proceedings of Construction Research Congress (CRC) 2018 (pp. 116-125) in New Orleans, LA, April 2-4, 2018.

Zhao, D., McCoy, A. P., Agee, P., Mo, Y., Reichard, G., & Paige, F. (2018). Time effects of green buildings on energy use for low-income households: A longitudinal study in the United States. Sustainable Cities and Society.

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