Master Thesis Research – Robot Learning Lab, Universität Freiburg
ImageBounding Box
Designed and evaluated a self-supervised model for object search in indoor environments using vision foundation model embeddings. Conducted large-scale experiments for AI training of object search behaviors. Focused on training, evaluation, and data preparation pipelines using neural network embeddings.
• Developed object search strategies leveraging embedding-based data labeling.
• Labeled datasets and evaluated classification boundaries in embedding space.
• Used PyTorch and vision-language models for AI training and fine-tuning.
• Wrote and submitted a research paper based on the labeled data and findings.
Designed and evaluated a self-supervised model for object search in indoor environments using vision foundation model embeddings. Conducted large-scale experiments for AI training of object search behaviors. Focused on training, evaluation, and data preparation pipelines using neural network embeddings. • Developed object search strategies leveraging embedding-based data labeling. • Labeled datasets and evaluated classification boundaries in embedding space. • Used PyTorch and vision-language models for AI training and fine-tuning. • Wrote and submitted a research paper based on the labeled data and findings.
2025 - 2026