Trujillo Alto, Puerto Rico

Sandra Rodriguez-Toledo

This inventor holds 1 USPTO granted patent. Top assignee: Amgen Inc.. Active years: 2026.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Sandra Rodriguez-Toledo. Retrieved from https://idiyas.com/inventor/sandra-rodriguez-toledo

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: Innovations of Sandra Rodriguez-Toledo

Introduction

Sandra Rodriguez-Toledo is an accomplished inventor based in Trujillo Alto, Puerto Rico. She has made significant contributions to the field of automated visual inspection through her innovative patent. Her work focuses on enhancing the accuracy and efficiency of visual inspections, which is crucial in various industries.

Latest Patents

Sandra holds a patent for the "Targeted application of deep learning to automated visual inspection equipment." This method improves the accuracy of automated visual inspections of vessels. In her approach, a vessel containing a sample is oriented so that a line scan camera captures a profile view of the edge of a stopper. A series of images is taken while the vessel spins, allowing for the generation of a two-dimensional image of the stopper's edge. This image is then processed using a trained neural network to determine the likelihood of defects in the sample.

Career Highlights

Sandra is currently employed at Amgen Inc., where she continues to develop innovative solutions in her field. Her work has garnered attention for its potential to revolutionize automated inspection processes.

Collaborations

One of her notable coworkers is Neelima Chavali, who also contributes to the advancements in their shared field.

Conclusion

Sandra Rodriguez-Toledo's innovative work in automated visual inspection exemplifies the impact of deep learning technologies in enhancing industrial processes. Her contributions are paving the way for more efficient and accurate inspection methods.

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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