- Research data needs for robot learning and physical AI systems and translate them into dataset and evaluation specifications.
- Define data schemas, annotations, ground truth, and quality standards across robotics data types.
- Design collection and review protocols for external data providers.
- Build tools and validation workflows to audit datasets, identify quality issues, and give providers actionable feedback.
- Run experiments and analyze model behavior to assess how data quality, coverage, and structure affect performance.
- Collaborate with research and engineering teams, and when needed with data vendors and buyers, to improve robotics data offerings.