CV

Research Scientist Profile

Ph.D. candidate in autonomous driving and robotics with 5+ years of experience in multi-sensor perception, cooperative infrastructure perception, motion planning, model predictive control, and V2X connected mobility.

Built and validated perception and planning systems on field-tested autonomous shuttles, roadside infrastructure networks, and indoor mobile robot platforms, with first-author publications and open-source project releases in autonomous driving and cooperative perception.

Education

• Ph.D. Candidate, Mechanical and Mechatronics Engineering, University of Waterloo, Sept. 2020 - Aug. 2026
  • GPA: 94/100
  • Advisor: Prof. Amir Khajepour; co-supervisor: Prof. Ehsan Hashemi
• Bachelor of Engineering, Vehicle Engineering, Beijing Institute of Technology, Sept. 2016 - June 2020
  • GPA: 92.16/100

Selected Publications

• CoInfra: A Large-Scale Cooperative Infrastructure Perception System and Dataset in Adverse Weather. Under review at Transportation Research Part C, 2026. [arXiv] [code]
• Real-World Deployment of Cloud Autonomous Mobility System Using 5G Networks for Outdoor and Indoor Environments. Under review at IEEE Intelligent Transportation Systems Magazine, 2026. [arXiv]
• SAP-CoPE: Social-Aware Planning using Cooperative Pose Estimation with Infrastructure Sensor Nodes. Revised manuscript under review at IEEE Transactions on Automation Science and Engineering, 2026. [arXiv] [code]
• A Novel Motion Planning for Autonomous Vehicles Using Point Cloud Based Potential Field. IEEE Transactions on Vehicular Technology, 2024. [DOI]
• An Efficient Approach to Generate Safe Drivable Space by LiDAR-Camera-HD Map Fusion. IEEE International Conference on Intelligent Transportation Systems, 2024. [DOI] [code]
• Enhancing Indoor Mobility with Connected Sensor Nodes: A Real-Time, Delay-Aware Cooperative Perception Approach. IEEE International Conference on Intelligent Transportation Systems, 2024. [DOI] [code]

See the Publications page and Google Scholar for the full list.

Research & Project Experience

Autonomous Driving Perception and Motion Planning, University of Waterloo, 2020 - 2024

• Developed LiDAR point-cloud potential-field and LiDAR-camera-HD map fusion methods for real-time drivable-space generation, road-boundary representation, obstacle avoidance, and efficient MPC-based trajectory generation considering vehicle dynamics, constraints, collision avoidance, and comfort.
• Validated perception and planning modules in simulation and on the WATonoBus full-scale autonomous shuttle, including complex road scenes and real-world operation in Canadian winter conditions.

Cooperative Infrastructure Perception (CoInfra), University of Waterloo, 2023 - Present

• Designed and deployed a 14-node roadside infrastructure network for adverse-weather traffic perception, city-scale data collection, cloud-side fusion, and globally consistent 3D tracking.
• Developed calibration, synchronization, latency compensation, delay-aware fusion, and large-scale dataset pipelines for vehicle-infrastructure cooperation and multi-agent perception research.
• Led technology transfer and deployment of nine intelligent sensor nodes for municipal intersection traffic monitoring and analysis in Waterloo, Kitchener, and Guelph, in collaboration with Prof. Liping Fu.

Edge-Cloud Cooperative Mobility for Vehicles and Mobile Robots, University of Waterloo, 2023 - Present

• Developed a Cloud-based Autonomous Mobility (CAM) framework that integrates distributed infrastructure sensor nodes, edge perception, 5G/Wi-Fi communication, and cloud-level fusion to provide shared scene understanding for connected autonomous vehicles and indoor mobile robots.
• Integrated cooperative 3D human perception and delay-aware tracking with closed-loop MPC planning on a real-world medical-bed robot platform for dynamic indoor environments, highlighted by UWaterloo News.

Autonomous Shuttle and Field Demonstrations, University of Waterloo, 2021 - 2025

• Led second-generation perception development and the transition from a custom in-house autonomy stack to an Autoware-based next-generation platform.
• Supported real-world demonstrations and media outreach, including ESV, MathWorks, and UWaterloo News.

Autonomous Farming Robotics, University of Waterloo, 2026 - Present

• Developing visual-LiDAR fusion methods and a modular sensor box for agricultural field localization, odometry robustness, crop detection, and tool anomaly detection.

Awards & Professional Service

• Awards: Velocity Up Start Award ($15,000, 2025); “Chunhui Cup” Innovation and Entrepreneurship Competition (2024); Mitacs Globalink Graduate Fellowship ($15,000, 2020); Outstanding Prize, RoboMaster 2020 AI Challenge - Perception (2020).
• Service: Session organizer and chair, IEEE ITSC 2024 technical session “Trustworthy Diagnosis in Connected Mobility”; reviewer for IEEE T-ITS, IEEE TVT, IEEE VTM, IEEE ITSC, and related IEEE venues.

Skills

• Programming: Python, C++, MATLAB/Simulink
• Robotics and Autonomous Driving: ROS1/ROS2, Autoware, MPC, motion planning, vehicle control
• Perception and Sensor Fusion: OpenCV, PCL, sensor calibration, multi-sensor fusion, cooperative perception, 3D object tracking, SLAM, V2X, uncertainty-aware perception
• Machine Learning: PyTorch, scikit-learn, TensorRT, deep learning, object detection, semantic segmentation
• Languages: Chinese (native), English (fluent)