Yong Kwon Cho

RICAL
Construction and Infrastructure Systems Engineering
Google Scholar
Publications

Yong Kwon Cho

Professor
Email Address
yong.cho@ce.gatech.edu
Telephone
404.385.2038
Office Building
Mason Building
Office Room Number
4140B
Biography

Dr. Yong Cho, MSCE ’97, is a Professor in the School of Civil and Environmental Engineering at the Georgia Institute of Technology, where he directs the Robotics and Intelligent Construction Automation Lab (RICAL) and is a core faculty member of the Institute for Robotics and Intelligent Machines (IRIM). He earned his Ph.D. from the University of Texas at Austin in 2000 and previously held faculty positions at the University of Nebraska–Lincoln and the University of Wisconsin–Platteville. A 2011 NSF CAREER Award recipient, his research focuses on construction automation, robotics, and computing for sustainable built environments. He serves as Co-Editor-in-Chief of the ASCE Journal of Computing in Civil Engineering and Vice President of the International Association for Automation and Robotics in Construction (IAARC), and is a recipient of the IAARC Tucker–Hasegawa Award and the 2024 ASCE Computing in Civil Engineering Award.

Research

With over 25 years of experience, Dr. Cho’s research advances construction robotics and field automation, with an emphasis on SLAM-based robot navigation, human–robot interaction, IoT-based worker safety and productivity monitoring, and edge computing for work-zone safety.

Education

Ph.D. in Civil Engineering

University of Texas at Austin

2000

M.S. in Civil Engineering

Georgia Tech 

1997

B.S. in Civil Engineering 

Inha University

1996

                         

Teaching

Dr. Cho’s teaching emphasizes integrating advanced construction technologies into core and graduate courses through hands-on learning and technology demonstrations. As new technologies emerge, he continuously updates course content to incorporate construction automation, robotics, sensing technologies, and research-driven learning, using active pedagogy that brings ongoing research directly into the classroom and helps students connect fundamental engineering principles with real-world practice in a rapidly evolving construction industry.

Distinctions & Awards
  • 2024, Woh Hup Distinguished Professor, Civil & Environmental Engineering, National University of Singapore (NUS)
  • 2024, ASCE Computing in Civil Engineering Award
  • 2022, Tucker-Hasegawa Award by the International Association for Automation and Robotics in Construction(IAARC).
  • 2018, Distinguished Professor for 2018 Award, Construction Industry Institute (CII) Annual Meeting, Indianapolis, IN, July 24.
  • 2015, Leadership in Use of Educational Technology Award at School of Civil and Environmental Engineering, Georgia Tech
  • 2014, Bill Schultz Junior Faculty Teaching Award at the School of Civil and Environmental Engineering, Georgia Tech
  • 2011, NSF Early Faculty CAREER Award from the Civil Infrastructure Systems (CIS) Program
Publications
  1. Kim, P., and Cho, Y. K. (2026). “Adaptive 3D scanning and view planning for autonomous mobile robots: Field implementation in cluttered and unknown environments.” ASCE Journal of Computing in Civil Engineering.
  2. Kim, Y., Chen, Y., Gombolay, M., and Cho, Y. (2025). “Understanding the effects of humanlike robot motions on unfocused human–robot interaction” Elsevier, Advanced Engineering Informatics, Vol. 68. https://doi.org/10.1016/j.aei.2025.103751
  3. Kim, Y., Kim, S., Chen, Y., Yang, H., Kim, S., Ha, S., Gombolay, M., Ahn, Y., and Cho, Y. (2024). “Understanding human-robot proxemic norms in construction: How do humans navigate around robots?” Automation in Construction, Vol. 164. DOI: 10.1016/j.autcon.2024.105455
  4. Kim, K.N., Jeong, I., and Cho, Y. (2023). “Signal processing and alert logic evaluation for IoT-based work zone proximity safety system.” ASCE Journal of Construction and Management. Vol. 149 (2). DOI: 10.1061/JCEMD4.COENG-12417
  5. Chen, J. and Cho, Y.K. (2022). “CrackEmbed: Point feature embedding for crack segmentation from disaster site point clouds with anomaly detection.” Advanced Engineering Informatics, volume 52, doi.org/10.1016/j.aei.2022.101550
  6. Park, J.S. and Cho, Y. (2022). "Point Cloud Information Modeling (PCIM): Deep Learning-based Automated Information Modeling Framework for Point Cloud Data." ASCE Journal of Construction Engineering and Management, 148(2), DOI: 10.1061/(ASCE)CO.1943-7862.0002227
  7. Chen, J., Kira, Z., and Cho, Y.K. (2021). "LRGNet: Learnable Region Growing for Class-Agnostic Point Cloud Segmentation." IEEE Robotics and Automation Letters. Accepted for oral presentation at the International Conference on Robotics and Automation (ICRA) 2021, doi: 10.1109/LRA.2021.3062607
  8. Price, L., Chen, J., Park, J., and Cho, Y.(2021). "Multisensor-driven real-time crane monitoring system for blind lift operations: Lessons learned from a case study." Automation in Construction, Vol 124 doi.org/10.1016/j.autcon.2021.103552
  9. Jeong, I., Jang, Y., Park, J.S., and Cho, Y. (2021). "Motion Planning of Mobile Robots for Autonomous Navigation on Uneven Ground Surfaces." ASCE Journal of Computing in Civil Engineering, in press
  10. Kim, K.N., and Cho, Y. (2021). "Automatic recognition of workers’ motions in highway construction by using motion sensors and long short-term memory (LSTM) networks." ASCE Journal of Construction Engineering and Management, 147(3), doi.org/10.1061/(ASCE)CO.1943-7862.0002001

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