Ation Lab
The suffix '-ation' embodies the process or action leading to generating outcomes - which is a fundamental aspect of research in engineering
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Research Interests
Building Information Modeling
Digitalization of the built environment (buildings & industrial facilities)
Automation in construction
Electrification
De-carbonization
Circular Economy
Computer Vision
Artificial Intelligence
Reality Capture (3D Laser Scanning)
Lab members (current)
Assistant Professor
Lab Director (2023 - Present) <jongwon.ma@yonsei.ac.kr>
Jong Won Ma
Jong Won Ma
Previous affiliation: Assistant Professor at Concordia University (2023 - 2025) / PhD in Civil Engineering at the University of Texas at Austin (2022) / MS & BS in Civil Engineering at Yonsei University (2018 & 2016)
My research interests revolve around the convergence of science, technology, and the built environment, with a particular focus on the digitalization of workflows leveraging artificial intelligence and computer vision. His specialty is in as-built Scan-to-Building Information Modeling, an automated approach for the digital transformation of existing infrastructure and building systems that employs reality capture technologies to generate a 3D digital replica of the physical world. His past research efforts include streamlining construction workflows by expanding the scope of advanced work packaging to encompass commissioning and startup processes, as well as enhancing local community resilience through a combination of qualitative and quantitative approaches. In addition to my studies, I find joy in various outdoor activities such as tennis, working out at the gym, and exploring new delicious restaurants.
PhD Program
(2023 - Present
<moaaz.elkabalawy@mail.concordia.ca>
Previous affiliation: MS in Civil Engineering at Concordia University / BS in Civil and Environmental Engineering at University of Sharjah
As a Ph.D. student, my primary focus encompasses the cutting-edge domain of modular offsite construction digitalization through computer vision technologies and exploring the broader spectrum of the 4.0 industrial revolution in digital construction. This multifaceted research interest is aimed at revolutionizing the construction industry by harnessing digital transformation tools to improve efficiency, accuracy, and sustainability. Beyond the confines of my research, I am a big fan of soccer reading, and hiking. While soccer supports my physical health and allows me to socialize with friends, reading opens the doors to diverse worlds of knowledge, culture, and imagination. As for hiking, it allows me to reconnect with nature to find peace away from the technological and digital pursuits of my professional life.
MS & PhD Program
(2024 - Present)
<deokyeong.kim@mail.concordia.ca>
Deokyeong Kim (Co-advised by Dr. Leila Kosseim)
Previous affiliation: BS in Computer Science at Concordia University
I have a background in computer science and a keen interest in Artificial Intelligence, machine learning, and deep learning. Currently, my primary focus lies in conducting Natual Language Processing research related to crane safety within the civil engineering domain. Through this research, I aim to contribute to solving and improving safety issues in industrial settings. Outside of my professional endeavors, I enjoy hobbies such as playing the guitar, baking, and golfing, which help me maintain a balance in life and engage in creative activities.
Lab members (Past)
Jun-Hyoung Park
Undergraduate Intern
(2024 -2025)
<jun-hyoung.park@mail.concordia.ca>
Xi Luo
MASc
(2025)
<xi.luo@mail.concordia.ca>
JOIN OUR LAB!!
Ation lab is seeking new talented team members for both MASc & PhD positions!
Please access this link for your application!
Past Research Projects
PI, University Student Research Award
Funding Agency: Natural Sciences and Engineering Research Council of Canada
Period: 2024/05 - 2024/08
Students: Jun-Hyoung Park
PI, RT423 - Enhancing Crane Safety: Mining Insights and Patterns for Predictive, Preventive, and Proactive Analysis
Funding Agency: Construction Industry Institute
Period: 2024/02 - 2024/08
Students: Deokyeong Kim
Co-PI, Electrified, Resilient, and Decarbonized Communities Grant - Eco-friendly Smart Construction Systems for Decarbonization of Construction Industry
Funding Agency: Canada First Research Excellence
Period: 2024/03 - 2026/03
Students: TBD (Hiring)
Co-PI, Electrified, Resilient, and Decarbonized Communities Grant - Digital Twins for Smart Decarbonization of the Built Environment Meeting Circular Economy Criteria
Funding Agency: Canada First Research Excellence
Period: 2024/03 - 2026/03
Students: TBD (Hiring)
PI, Discovery Grant - Digitalization of Industrial Facilities using Scan-to-BIM
Funding Agency: Natural Sciences and Engineering Research Council of Canada
Period: 2023/04 - 2028/03
Students: Moaaz Elkabalawy & Xi Luo
Publications
Ma, J.W.*; Jung, J.; Leite, F. (2024) “Deep Learning-based Scan-to-BIM Automation and Object Scope Expansion using a Low-Cost 3D Scan Data”, Journal of Computing in Civil Engineering
Ma, J.W.*; Leite, F.; Lieberknecht, K.; Stephens, K.; Bixler, R.P. (2024) “Using Q-methodology to Discover Disaster Resilience Perspectives from Local Residents”, International Journal of Disaster Risk Reduction
Lee, Y.; Ma, J.W.; Leite, F. (2023) “A Parametric Approach Towards Semi-Automated 3d As-Built Modeling", Journal of Information Technology in Construction, https://doi.org/10.36680/j.itcon.2023.041
Park, S.; Ma, J.W.* (2023) “Voxel-based Structural Monitoring Model for Building Structures Using Terrestrial Laser Scanning”, Journal of Building Engineering, https://doi.org/10.1016/j.jobe.2023.108151
Ma, J.W.*; Czerniawski, T.; Leite, F. (2022) Chapter: Automated Scan-to-BIM, Research Companion on Building Information Modeling (Wiley), https://dx.doi.org/10.4337/9781839105524
Ma, J.W.*; Leite, F. (2022) “Performance boosting of conventional deep learning-based semantic segmentation leveraging unsupervised clustering”, Automation in Construction, https://doi.org/10.1016/j.autcon.2022.104167
O’Connor, J. T.; Leite, F.; Ma, J.W.* (2022) “Expanding the Advanced Work Packaging Scope to include Commissioning and Startup for Industry Projects”, Construction Innovation, https://doi.org/10.1108/CI-09-2021-0173
Ma, J.W.*; Czerniawski, T.; Leite, F. (2021) “An Application of Metadata-based Image Retrieval System for Facility Management”, Advanced Engineering Informatics, https://doi.org/10.1016/j.aei.2021.101417
Han, B.; Ma, J.W.; Leite, F. (2021) “A Framework for Automatically Identifying Occluded Objects in 3D Models: Towards Comprehensive Construction Design Review in Virtual Reality”, Advanced Engineering Informatics, https://doi.org/10.1016/j.aei.2021.101398
Ju, S.; Lim, H.; Ma, J.W.; Kim, S.; Lee, K.; Zhao, S.; Heo, J. (2021) “Optimal County-level Crop Yield Prediction Using MODIS-based Vegetation Indices and Weather Data: A Comparative Study on Machine Learning Models”, Agricultural and Forest Meteorology, https://doi.org/10.1016/j.agrformet.2021.108530
Czerniawski, T.; Ma, J.W.; Leite, F. (2021) “Automated Building Change Detection with Amodal Completion of Point Clouds”, Automation in Construction, https://doi.org/10.1016/j.autcon.2021.103568
Ma, J.W.*; Czerniawski, T.; Leite, F. (2020) “Semantic Segmentation of Point Clouds of Building Interiors with Deep Learning: Augmenting Training Datasets with Synthetic BIM-based Point Clouds”, Automation in Construction, https://doi.org/10.1016/j.autcon.2020.103144
Ma, J.W.; Nguyen, C.H.; Lee, K.; Heo, J. (2019) “Regional-Scale Rice Yield Estimation Using Stacked Auto-encoder with Climatic and MODIS data: a case study of South Korea”, International Journal of Remote Sensing, https://doi.org/10.1080/01431161.2018.1488291
Ma, J.W.; Lee, K.; Choi. K.; Heo, J. (2017) “Rice Yield Estimation of South Korea from Year 2003-2016 Using Stacked Sparse AutoEncoder”, Korean Journal of Remote Sensing, https://doi.org/10.7780/kjrs.2017.33.5.2.3
Nguyen, M.H.; Ma, J.W.; Lee, K.; Heo, J. (2017) “The Design of Web-based Crop Information System Using Open-Source Framework and Remotely Sensed Data”, Korean Journal of Remote Sensing, https://doi.org/10.7780/kjrs.2017.33.5.2.14
Nguyen, M.H.; Ju, S.; Ma, J.W.; Heo, J. (2017) “A Benchmark Test of Spatial Big Data Processing Tools and a MapReduce Application”, Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography, https://doi.org/10.7848/ksgpc.2017.35.5.405
Ma, J.W.; Nguyen, C.H.; Lee, K.; Heo, J. (2016) “Convolutional Neural Networks for Rice Yield Estimation Using MODIS and Weather Data: A Case Study for South Korea”, Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography, https://doi.org/10.7848/ksgpc.2016.34.5.525
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