Oakland, CA, United States of America

Caydie Tran

This inventor holds 1 USPTO granted patent and 1 published patent application. Top assignee: Apollo Graph, Inc.. Active years: 2025.

USPTO Granted Patents = 1 

% Patents Active = 100.0

Average Co-Inventor Count = 10.0

ph-index = 1


Company Filing History:


Years Active: 2025

Loading Chart...
1 patent (USPTO):Explore Patents

Title: Caydie Tran: Innovator in Queryable Supergraph Subset Representations

Introduction

Caydie Tran is a notable inventor based in Oakland, CA. He has made significant contributions to the field of computer science, particularly in the area of graph representations. His innovative work has led to the development of a patent that enhances the way data is queried and represented.

Latest Patents

Caydie Tran holds a patent titled "Infrastructure for Queryable Supergraph Subset Representations." This patent focuses on creating an apparatus that utilizes at least one processor of a computing device to manage source graph schemas. The invention allows users to specify filters to generate subset representations of the source graph schema. It also provides controlled access to these representations for specific entities, ensuring that sensitive information remains protected.

Career Highlights

Caydie Tran is currently employed at Apollo Graph, Inc., where he continues to push the boundaries of technology and innovation. His work at Apollo Graph has positioned him as a key player in the development of advanced graph technologies. With a patent portfolio that includes 1 patent, he is recognized for his contributions to the field.

Collaborations

Caydie has collaborated with talented individuals such as Adam Samuel Zionts and Joshua Rohan Segaran. These partnerships have fostered a creative environment that encourages innovation and the sharing of ideas.

Conclusion

Caydie Tran's work in queryable supergraph subset representations exemplifies the impact of innovative thinking in technology. His contributions continue to shape the future of data management and representation.

This text is generated by artificial intelligence and may not be accurate.
Please report any incorrect information to [email protected]
Loading…