Mountain View, CA, United States of America

Linh Mai Tran


Average Co-Inventor Count = 4.0

ph-index = 1


Company Filing History:


Years Active: 2025

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1 patent (USPTO):Explore Patents

Title: The Innovative Mind of Linh Mai Tran

Introduction

Linh Mai Tran is an inventive force based in Mountain View, CA. With a focus on advancements in machine learning and natural language processing, he has made significant contributions to the field through his inventive spirit and technical expertise.

Latest Patents

Linh is credited with one notable patent titled "Learning to extract entities from conversations with neural networks." This innovative work encompasses methods, systems, and apparatus, including computer programs encoded on computer storage media, for extracting entities from conversation transcript data. One of the described methods involves obtaining a conversation transcript sequence and processing it using a span detection neural network. This network generates a set of text token spans, which are further analyzed through neural networks to obtain entity name and status probability distributions, enhancing the understanding of conversational context.

Career Highlights

Currently, Linh Mai Tran is employed at Google Inc., where he continues to develop advanced technologies. His work reflects a deep commitment to leveraging neural networks for improving how machines understand human language.

Collaborations

Throughout his career, Linh has had the opportunity to collaborate with brilliant minds including Nan Du and Yu-hui Chen. These collaborations have allowed for a dynamic exchange of ideas and innovation, driving the development of cutting-edge solutions within the tech industry.

Conclusion

Linh Mai Tran stands out as an influential inventor in the realm of machine learning and natural language processing. His patent highlights his pioneering approach to extracting meaningful insights from conversational data, underscoring his role as a key player in innovations at Google Inc. As technology continues to evolve, Linh's contributions are likely to have a lasting impact on the way we interact with machines.

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