PhD Research Intern, Multi-Modal Foundation Encoder for Perception
Tasks
- Build live maps representation
- Develop multi modal foundation encoder
- Enable zero shot detection via radar language grounding
- Explore self supervised pre training
- Implement efficient sensor fusion with cross attention
- Improve robustness to adverse weather and occlusion
- Integrate 3D Gaussian splats for dynamic geometry
- Support 3D object detection and tracking
- Support 3D segmentation occupancy
- Train foundation models for long tail perception
Perks/Benefits
Skills/Tech-stack
3D Object Detection | 3D Tracking | 3D segmentation | Autonomous Driving | Computer Vision | Cross-Attention | Deep learning | Gaussian Splatting | Language Models | Large Language Models | Lidar | Masked Modeling | Multi-Modal | Multi-Modal Learning | Object Detection | Occupancy prediction | Radar | Radar Object Detection | Self-Supervised Learning | Self-supervised | Sensor fusion | Supervised Learning | Vision Language Models | Vision-language | Voxel Grid | Zero-Shot | Zero-shot Learning
Education
Roles
Regions
Countries
States
Cities
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