Paris, France

Sarah Najmark

This inventor holds 1 USPTO granted patent. Top assignee: Gdm Holding LLC. Active years: 2026.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Sarah Najmark. Retrieved from https://idiyas.com/inventor/sarah-najmark-8tjaodav

Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile


Average Co-Inventor Count = 1.0

ph-index = 1


Company Filing History:


Years Active: 2026

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1 patent (USPTO):Explore Patents

Title: Sarah Najmark and On-Robot Data Collection.

Introduction

Sarah Najmark is an inventor associated with Paris, France. Her listed patent concerns methods for selecting robot sensor data for human annotation and for training machine-learning models that help operate robots.

Latest Patents

The provided information lists one patent for Najmark: “On-robot data collection.” The invention describes an on-robot controller that can select sensor data for transmission to a remote system when it detects cross-modal inconsistency, a recent task failure, or low confidence in a model output. The selected data can then be reviewed by people or used to update the robot’s machine-learning models.

The system may also use embedding vectors that represent shared characteristics across sensor-data sets. A robot can compare new sensor data with transmitted embeddings and send data for annotation or model updates when the embeddings are sufficiently similar. Najmark’s listed patent count is 1 patent.

Career Highlights

The supplied information associates Najmark with Gdm Holding LLC. It does not provide further details about her role, career history, or other inventions.

Collaborations

The patent description identifies a workflow involving robots, remote systems, and human annotators. The supplied information does not specify particular collaborators or organizations beyond Gdm Holding LLC.

Conclusion

Sarah Najmark’s listed invention focuses on selecting useful robot sensor data for annotation and machine-learning improvements, linking on-robot decision-making with remote review and model updates.

Profile summary based on public USPTO records.
Data Sources: USPTO Patent Grant XML, Patent Center, EPO & CIPO • Normalized by IDiyas Innovation Graph. Methodology & provenance architecturePlease report any incorrect information to [email protected]
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