Salt Lake City, UT, United States of America

Travis Bennett Martin


Average Co-Inventor Count = 9.0

ph-index = 1


Company Filing History:


Years Active: 2025

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1 patent (USPTO):Explore Patents

Title: Innovations of Travis Bennett Martin

Introduction

Travis Bennett Martin is an accomplished inventor based in Salt Lake City, UT. He has made significant contributions to the field of data management and storage through his innovative patent. His work focuses on enhancing the efficiency and flexibility of handling high-volume object data, particularly in the realm of machine learning.

Latest Patents

Travis holds a patent titled "Cross-platform flexible data model for dynamic storage, management, and retrieval of high-volume object data." This patent describes systems, non-transitory computer-readable media, and methods that implement a cross-platform flexible data model. The invention aims to facilitate the dynamic storage, management, and retrieval of high-volume object data, including multi-modal machine learning datasets. The disclosed systems operate across various non-tabular media and multiple digital repository platforms, allowing for efficient management of machine learning datasets through a centralized metadata database.

Career Highlights

Travis is currently employed at Recursion Pharmaceuticals, Inc., where he applies his expertise in data management to support innovative research and development. His work at Recursion Pharmaceuticals emphasizes the importance of effective data handling in advancing medical research and technology.

Collaborations

Travis collaborates with talented individuals such as Jill Theresa Vandenbosch and Conrad Banneker Owen, contributing to a dynamic work environment that fosters innovation and creativity.

Conclusion

Travis Bennett Martin's contributions to the field of data management through his patent and work at Recursion Pharmaceuticals highlight the importance of innovation in technology. His efforts in developing a cross-platform flexible data model are paving the way for advancements in machine learning and data handling.

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