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Young Joon Suh
Senior Research Scientist specializing in AI for autonomous driving and semiconductors
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About
Robotics perception engineer focused on autonomous driving 3D detection, integrating PETR embeddings into BEVFormer and tackling hard orientation/temporal alignment issues in multi-camera BEV pipelines. Uses Gazebo with custom sensor plugins to validate calibration, timing, and transforms, and blends synthetic labels with real imagery for scalable 3D box generation.
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Key Strengths
- Deep familiarity with BEV-based multi-camera 3D perception (PETR + BEVFormer integration)
- Hands-on debugging of training issues (loss plateau; bounding box orientation errors)
- Temporal alignment strategies for fast-moving scenes (timestamping, pose interpolation, velocity propagation)
- Simulation-driven validation of calibration and timing (intrinsics/extrinsics, transforms, synchronization)
- Custom Gazebo sensor plugin work for realistic sensor effects (motion blur, exposure noise, rolling shutter)
- Bandwidth-aware distributed robotics approach (sharing semantic intent like 3D boxes/BEV grids)
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3 publications
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