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Jeongeun Lee
Mid-level AI/Robotics Engineer specializing in autonomous systems and perception
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Robotics software engineer in an Autonomous Vehicle Lab building an end-to-end ROS 2 autonomous golf cart stack (sensor integration, SLAM, planning, and camera+LiDAR perception). Demonstrated strong systems-level debugging by fixing a FastLIO2 LiDAR timestamp/IMU-window issue that restored mapping quality, and stabilized real-time GigE camera perception by diagnosing backpressure and tuning ROS 2 QoS plus compressed transport.
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Key Strengths
- End-to-end autonomous stack integration (sensors, drivers, ROS2/DDS)
- Deep debugging of SLAM/localization timing issues (FastLIO2 LiDAR timestamp mismatch) with validated mapping improvement
- Real-time perception pipeline performance troubleshooting (frame drops/latency) using rate vs timestamp analysis and backpressure tracing
- ROS 2 systems engineering: custom nodes/packages for timestamps, TF static, planning, and perception
- Distributed robotics communication setup across heterogeneous compute modules using CycloneDDS and ROS Domain ID isolation
- Reproducible deployment via Docker/Docker Compose containerization of ROS2 stack and sensor drivers
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Experience
Education
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Publications
1 publication
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Mid-level Software Engineer specializing in MLOps, AI infrastructure, and distributed systems
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