Hello! 你好！
Welcome to my academic website! I’m Xiayu Zhao, a PhD student in Civil and Environmental Engineering at the University of Illinois Urbana-Champaign, working in the Robotic, Automation, and Intelligent Sensing (RAISe) Lab under the supervision of Dr. Houtan Jebelli. I work closely with Dr. Yizhi Liu.
About My Research
My research focuses on AI and robotics for construction applications, with particular emphasis on:
- AI and Machine Learning for Human-Robot Collaboration: Developing algorithms that enable seamless collaboration between humans and robots in construction environments
- Computer Vision for Automated Inspection: Creating computer vision techniques for automated inspection tasks, including real-time roof defect segmentation
- Construction Robotics: Advancing robotic construction technologies, including 3D printing, robotic control, and navigation systems
- Digital Architecture and Computational Design: Exploring computational design methods and their integration with robotic fabrication
- Immersive Technologies for Safety Training: Developing VR-based training systems for construction safety, particularly for human-robot collaborative scenarios
My work combines robotics, computer vision, machine learning, and human-computer interaction to improve construction safety, efficiency, and quality. I have experience in developing software interfaces for robotic construction, programming robot arms for large-scale 3D printing, and creating immersive training environments using ROS and Unity.
Education
- PhD Student, Civil and Environmental Engineering, University of Illinois Urbana-Champaign
- Spring 2024 - present
- Advisor: Dr. Houtan Jebelli
- GPA: 3.87/4.00
- Robotic, Automation, and Intelligent Sensing (RAISe) Lab
- Master of Architecture, Tsinghua University, Beijing, China (2019 - 2021)
- Bachelor of Architecture, Tianjin University, Tianjin, China (2014 - 2019)
Research Experience
I am currently working on several projects in the RAISe Lab, including:
- Real-time roof defect segmentation using deep learning (RRD-SegNet)
- Adaptive intelligence for robot navigation efficiency using deep reinforcement learning
- Grounding large language models in robot control for human-robot collaboration
Previously, I worked as a Research Engineer at the Institute of Future Human Habitats at Tsinghua University, where I developed large-scale robotic construction technologies and software interfaces for robotic control.
News
- Multiple papers accepted to the 2024 International Conference on Computing in Civil Engineering (i3CE)
- Paper on real-time roof defect segmentation submitted to Computer‐Aided Civil and Infrastructure Engineering (under review)