SangHyun Lee

I am leading the Dynamic Project Management (DPM) Group at the University of Michigan, which aims to understand and manage construction dynamics and human-infrastructure interface through sensing, data analytics and computer simulation. Particularly, DPM is interested in achieving the maximum benefit from technologies like wearables, automation and robotics for humans in construction and infrastructure. DPM also applies these technologies to direct smart and connected communities and cities toward social equality. For more information, please visit: http://dpm.engin.umich.edu.

• Founder and President of Kinetica Labs
• Director of U-M Construction Industry Alliance Program
• Distinguished Visiting Professor, Hangyang University, Korea
• Affiliated Faculty in Michigan Robotics
• Affiliated Faculty in Energy Institute
• Affiliated Faculty in Graham Sustainability Institute
• Affiliated Faculty in Michigan Institute of Computational Discovery and Engineering
• Board of Governors, ASCE Construction Institute (2014-2015)
• Chair, ASCE Construction Research Council (2013-2014)
• Chair, ASCE TCCIT Visualization, Information Modeling and Simulation Committee (2013-2015)
• Associate Editor, ASCE Journal of Computing in Civil Engineering (2008-present)
• Specialty Editor, ASCE Journal of Construction Engineering and Management (2008-present)

• Henry Russel Award, University of Michigan, 2015
• Distinguished Professor Award, Construction Industry Institute, 2015
• FIATECH Outstanding Early Career Research Award, 2015
• ASCE Thomas Fitch Rowland Prize, 2014
• ASCE Daniel W. Halpin Award for Scholarship in Construction, 2014
• Best Paper Award, ASCE Journal of Computing in Civil Engineering
• Stephen G. Revay Award, Canadian Society for Civil Engineering, 2012
• Best Paper Award, ASCE International Conference on Computing in Civil Engineering, 2012

Please see all publications from https://dpm.engin.umich.edu/publications/. Selected ones are:

• Jebelli, H., Khalili, M., and Lee, S. “A Continuously Updated, Computationally Efficient Stress Recognition Framework Using Electroencephalogram (EEG) by Applying Online Multi-Trask Learning Algorithms (OMTL).” Journal of Biomedical and Health Informatics, IEEE, (Accepted).
• You, S., Kim, J., Lee, S., Kamat, V., and Robert, L. “Enhancing Perceived Safety in Human–Robot Collaborative Construction Using Immersive Virtual Environments.” Automation in Construction, Elsevier, Vol. 96, pp. 161-170.
• Jebelli, H., Hwang, S., and Lee, S. (2018) “EEG-based Workers’ Stress Recognition at Construction Sites.” Automation in Construction, Elsevier, Vol. 93, pp. 315-324.
• Choi, B. and Lee, S. (2017)  “An Empirically Based Agent-Based Model of the Socio-Cognitive Process of Construction Workers’ Safety Behavior.” Journal of Construction Engineering and Management, ASCE, Vol. 144
• Hwang, S. and  Lee, S. (2017) “Wristband-type Wearable Health Devices to Measure Construction Workers’ Physical Demands.” Automation in Construction, Elsevier Science, New York, NY, Vol. 83, pp 330-340
• Anderson, K., Song, K., Lee, S., Krupka, E., Lee, H., and Park, M. (2017) “Longitudinal Analysis of Normative Energy Use Feedback On Dormitory Occupants.” Applied Energy, Elsevier Science, New York, NY, Vol. 189, pp 623-639
• Alwasel, A., Abdel-Rahman, E., Haas, C., and Lee, S. (2017) “Experience, Productivity, and Musculoskeletal Injury among Masonry Workers.” Journal of Construction Engineering and Management, ASCE, Reston, VA, Vol. 143, No. 6, 05017003
• Choi, B., Ahn, S., and Lee, S. (2017) “The Role of Social Norms and Social Identifications in Construction Workers’ Safety Behavior I: Theory for Safety Behavior.” Journal of Construction Engineering and Management, ASCE, Reston, VA, Vol. 143, No. 5, 04016124
• Anderson, K. and Lee, S. (2016) “An Empirically Grounded Model for Simulating Normative Energy Use Feedback Interventions” Applied Energy, Elsevier Science, New York, NY, Vol. 173, pp 272-282
• Seo, J., *Han, S., Lee, S. and Kim, H. (2015) “Computer Vision Techniques for Construction Safety and Health Monitoring.” Advanced Engineering Informatics, Elsevier Science, New York, NY, Vol. 29 No. 2, pp. 239-251.