Published in arXiv preprint arXiv:2509.16204, 2025
This paper benchmarks the engineering design capabilities of large language models toward engineering AGI.
Recommended citation: Guo, X., Li, Y., Kong, X., Jiang, Y., Zhao, X., Gong, Z., Zhang, Y., Li, D., Sang, T., et al. (2025). "Toward engineering AGI: Benchmarking the engineering design capabilities of LLMs." arXiv preprint arXiv:2509.16204.
Download Paper
Published in ASCE OPEN: Multidisciplinary Journal of Civil Engineering, 2025
This paper presents a module-enhanced, slope-adaptive, and hazard-aware hexapod robotic system for safe roof inspection.
Recommended citation: Zhao, X., Liu, Y., and Jebelli, H. (2025). "Module-Enhanced Slope-Adaptive and Hazard-Aware Hexapod Robotic System for Safe Roof Inspection." ASCE OPEN: Multidisciplinary Journal of Civil Engineering, 3(1), 04025011.
Download Paper
Published in Computer-Aided Civil and Infrastructure Engineering, 2025
This paper presents RRD-SegNet, a computational method for real-time roof defect segmentation in robotic inspection applications.
Recommended citation: Zhao, X. and Jebelli, H. (2025). "A computational method for real-time roof defect segmentation in robotic inspection." Computer-Aided Civil and Infrastructure Engineering, 40(23), 3596-3623.
Download Paper
Published in Architectural Intelligence, 2022
This paper explores biomimetic design inspired by tafoni (honeycomb-like rock formations) for creating porous architectural spaces using computational design methods.
Recommended citation: Ye, W., Chen, S., Zhao, X., Xu, W. (2022). "Porous Space — Biomimetic of Tafoni in Computational Design." Architectural Intelligence, 18 (2022).
Download Paper
Published in Chinese & Overseas Architecture, 2021
This paper reviews the research progress and application status of 3D printing construction technology.
Recommended citation: Zhao, X., Xu, W. (2021). "Research Progress and Application Status of 3D Printing Construction Technology." Chinese & Overseas Architecture, 10(2021):7-13.
Download Paper
Published in Computing in Civil Engineering 2025: Computational and Intelligent, 2026
This paper presents an LLM-driven framework for safe robotic navigation in construction sites using prompt engineering and terrain-adaptive path planning.
Recommended citation: Zhao, X., Ren, T., and Jebelli, H. (2026). "LLM-Driven Safe Robotic Navigation in Construction Sites: A Prompt Engineering Framework with Terrain-Adaptive Path Planning." Computing in Civil Engineering 2025: Computational and Intelligent.
Download Paper
Published in Computing in Civil Engineering 2025: Resilient, Robotic, and Educational, 2026
This paper presents dynamic robotic control strategies for maintaining UAV stability when carrying rotatory payloads.
Recommended citation: Ren, T., Zhao, X., and Jebelli, H. (2026). "Dynamic Robotic Control Strategies for UAV Stability with Rotatory Payload." Computing in Civil Engineering 2025: Resilient, Robotic, and Educational.
Download Paper
Published in Computing in Civil Engineering 2025: Resilient, Robotic, and Educational, 2026
This paper presents a hybrid UAV-UGV system with interchangeable ground modules for multi-terrain construction site inspection.
Recommended citation: Zhao, X., Liu, Y., and Jebelli, H. (2026). "Hybrid UAV-UGV System with Interchangeable Ground Modules for Multi-Terrain Construction Site Inspection." Computing in Civil Engineering 2025: Resilient, Robotic, and Educational.
Download Paper
Published in ISARC Proceedings of the International Symposium on Automation and Robotics in Construction, 2025
This paper presents advanced sensor integration methods for enhanced flight control in UAV-based construction automation.
Recommended citation: Ren, T., Zhao, X., and Jebelli, H. (2025). "Advanced Sensor Integration for Enhanced Flight Control in UAV-Based Construction Automation." ISARC. Proceedings of the International Symposium on Automation and Robotics in Construction.
Download Paper
Published in Computing in Civil Engineering 2024, 2025
This paper reviews machine learning-based optimization methods for modular robotic systems in construction.
Recommended citation: Liu, J., Ping, Y., Wang, Y., and Zhao, X. (2025). "Machine Learning-Based Optimization for Modular Robotic Systems in Construction: A Review." Computing in Civil Engineering 2024, 851-860.
Download Paper
Published in 42nd International Symposium on Automation and Robotics in Construction (ISARC), Montreal, 2025
This paper presents adaptive kinematic and dynamic control strategies for hexapod robots operating in complex construction environments.
Recommended citation: Zhao, X. and Jebelli, H. (2025). "Adaptive kinematic and dynamic control for hexapod robots in complex construction environments." Proc., 42nd Int. Symp. on Automation and Robotics in Construction, Montreal.
Download Paper
Published in 42nd International Symposium on Automation and Robotics in Construction (ISARC), 2025
This paper presents sensor fusion and a hierarchical inspection strategy for an aerial-ground multi-robot system.
Recommended citation: Zhao, X., Ren, T., Liu, Y., and Jebelli, H. (2025). "Sensor fusion and hierarchical inspection strategy for aerial-ground multi-robot system." 42nd International Symposium on Automation and Robotics in Construction (ISARC).
Download Paper
Published in 2024 International Conference on Computing in Civil Engineering (i3CE), 2024
This study investigates how exoskeleton systems affect the metabolic cost of workers during common repetitive construction tasks.
Recommended citation: Ojha, A., Gautam, Y., Zhao, X., Sharifironizi, A., Jebelli, H., and Martin, A. (2024). "Understanding the Impact of an Exoskeleton System On Metabolic Cost of Workers During Common Repetitive Construction Tasks." 2024 International Conference on Computing in Civil Engineering (i3CE), Pittsburgh, Pennsylvania, U.S. (Accepted).
Download Paper
Published in 2024 International Conference on Computing in Civil Engineering (i3CE), 2024
This paper presents a transfer learning approach to improve heat strain prediction in construction workers, addressing challenges related to individual variability.
Recommended citation: Ojha, A., Zhao, X., Zhang, Y., Liu, Y., and Jebelli, H. (2024). "Improving Heat Strain Prediction in Construction Workers: A Transfer Learning Approach to Overcome Variability Challenges." 2024 International Conference on Computing in Civil Engineering (i3CE), Pittsburgh, Pennsylvania, U.S. (Accepted).
Download Paper
Published in 2024 International Conference on Computing in Civil Engineering (i3CE), 2024
This paper explores how large language models can be grounded in robot control systems to facilitate human-robot collaboration in construction environments.
Recommended citation: Zhao, X., and Jebelli, H. (2024). "Grounding Large Language Models in Robot Control: Facilitating Human-Robot Collaboration in Construction." 2024 International Conference on Computing in Civil Engineering (i3CE), Pittsburgh, Pennsylvania, U.S. (Accepted).
Download Paper
Published in 2024 International Conference on Computing in Civil Engineering (i3CE), 2024
This paper presents an adaptive intelligence system for improving robot navigation efficiency using deep reinforcement learning in a cyber-physical system framework.
Recommended citation: Zhao, X., Ren, T., and Jebelli, H. (2024). "Adaptive Intelligence for Robot Navigation Efficiency with a Deep-Reinforcement-Learning-Based Cyber-Physical System." 2024 International Conference on Computing in Civil Engineering (i3CE), Pittsburgh, Pennsylvania, U.S. (Accepted).
Download Paper
Published in Hybrid Intelligence: Proceedings of the 4th International Conference on Computational Design and Robotic Fabrication (CDRF 2022), 2022
This paper presents a simulation algorithm based on weathered rock morphology and an optimization algorithm for design applications.
Recommended citation: Ye, W., Zhao, X., Xu, W. (2022). "Simulation Algorithm Based on Weathered Rock Morphology and Optimization Algorithm for Design Applications." in Hybrid Intelligence: Proceedings of the 4th International Conference on Computational Design and Robotic Fabrication (CDRF 2022). Online and Global, 2022.
Download Paper