Palo Alto, CA, United States of America

Lu Sun

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

IDiyas Innovation Intelligence. (2026). Inventor Profile: Lu Sun. Retrieved from https://idiyas.com/inventor/lu-sun-jjjnccck

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

Calculating rank

Average Co-Inventor Count = 1.0

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Company Filing History:


Years Active: 2026

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1 patent (USPTO):Explore Patents

Title: Lu Sun and Automatic Ontology Generation by Embedding Representations.

Introduction

Lu Sun is an inventor associated with Palo Alto, California, and Mercari, Inc. The patent information provided credits Sun with 1 patent, concerning a method for generating ontologies automatically from embedding representations.

Latest Patents

Sun’s listed patent, “Automatic Ontology Generation by Embedding Representations,” describes system, method, and computer-readable storage medium embodiments. The system receives a vectorized feature set derived from an embedding and supplies it to a set of fusers. It then generates a representation, derives tasks with corresponding qualifiers—including weights, loss functions, and feedforward functions—and computes weighted losses. Finally, it uses backpropagation through the fusers, feature set, embedding, or a combination of these components to produce a data model.

Career Highlights

The available information identifies Sun’s work with Mercari, Inc., and highlights an invention focused on embedding-based ontology generation. The described approach combines multiple features and task-specific learning objectives to produce a data model.

Collaborations

Sho Arora and Jeffrey Kenichiro Hara are listed as Sun’s coworkers. The information provided does not specify whether they collaborated on this patent.

Conclusion

Lu Sun’s listed patent presents an approach to automatic ontology generation that uses embedding-derived features, task-specific weighted losses, and backpropagation to create a data model.

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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