Faculty of Engineering
Research project description
Computer Vision for Smart Structure Laboratory (CVISS) at the University of Waterloo, led by Dr. Chul Min Yeum, invites applications for graduate studies (Direct Ph.D. and Ph.D.) in Civil and Environmental Engineering. Our lab focuses on practical, application-driven research, utilizing advanced technologies to integrate intelligence into the physical built environment, aiming to bolster infrastructure safety and resilience.
This position focuses on developing mobile robotic sensing and analysis systems, including unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs), for infrastructure inspection and management. Additionally, the role involves designing intuitive human-robot interaction frameworks for collaborative inspection and teleoperation. Students who have experience in mobile robotics, computer vision, and augmented/virtual reality are recommended to apply for this position.
Fields of research
- Robotics
- Computer Vision
- Image Processing
- AR/VR
Qualifications and ideal student profile
Prospective graduate student researchers must meet or exceed the minimum admission requirements for the programs connected to this opportunity. Visit the program pages using the links on this page to learn more about minimum admission requirements. In addition to minimum requirements, the research supervisor is looking for the following qualifications and student profile.
Requirements
- An undergraduate, MASc, or Ph.D. degree in Civil Engineering, Computer Science, Electrical Engineering, Mechatronics Engineering, Software Engineering, or Systems Engineering.
- Proven expertise in drone development, including flight control systems (e.g., PX4, ArduPilot), autonomous mission design, and execution.
- Comprehensive knowledge of UAV/UGV hardware, sensors, and communication protocols, including TCP/UDP and MAVLink.
- Experience with robot control algorithms for aerial and ground robotics applications.
- Familiarity with Robot Operating System (ROS) 1 & 2 for robotic system integration.
- Knowledge in computer vision, including multiview geometry, SLAM, and sensor fusion.
- Experience in AR/VR development within game engines (e.g., Unity).
- Proficiency in programming languages such as Python, C++, C, and C# for robotics and perception tasks.
- Proficiency in English, both spoken and written, for effective communication.
Preferred Qualifications
- Track record of publications in computer vision, image processing, and structural health monitoring.
- Experience in designing RTOS and GPU-accelerated computer vision algorithms.
- Proficiency in operating and manipulating optical sensors (e.g., color cameras, depth cameras, LiDAR) and sensing hardware (e.g., DAQ).
- Experience in developing video streaming applications (e.g., WebRTC, RTSP/RTMP, HTTP) is a plus.
- Prior experience with drone piloting is an advantageous asset.
- Familiarity with Git for version control is preferred.
Faculty researcher and supervisor
- Chul Min Yeum
Associate Professor, Department of Civil and Environmental Engineering
View faculty profile →
Computer Vision for Smart Structure (CViSS) Lab →
Graduate programs connected to this project
Important dates
Drone-Based Computer Vision for Infrastructure Inspection is an open and ongoing research opportunity. Expressions of interest can be submitted for any term.