Sunnyvale, CA, United States of America

Rahul Dilip Jagad

USPTO Granted Patents = 1 

Average Co-Inventor Count = 8.0

ph-index = 1

Forward Citations = 1(Granted Patents)


Company Filing History:


Years Active: 2023

where 'Filed Patents' based on already Granted Patents

1 patent (USPTO):

Title: Innovations by Rahul Dilip Jagad

Introduction

Rahul Dilip Jagad is an accomplished inventor based in Sunnyvale, California. He has made significant contributions to the field of technology, particularly in the processing of user profiles. His innovative approach leverages specialized data structures for graphical processing units (GPUs), enhancing the efficiency of user profile management.

Latest Patents

Rahul holds a patent for "Enhanced processing of user profiles using data structures specialized for graphical processing units (GPUs)." This patent discloses techniques for processing user profiles using data structures optimized for GPU processing. The methods involve evaluating characteristics of user profiles to determine whether to offload certain profiles to the GPU or process them locally using central processing units (CPUs). This innovation includes comparing interest tags in user profiles with logic trees, such as those representing marketing campaigns, to identify matching user profiles.

Career Highlights

Rahul is currently employed at Oracle International Corporation, where he applies his expertise in technology and innovation. His work focuses on improving user profile processing, which is crucial for enhancing user experience and operational efficiency in various applications.

Collaborations

Some of Rahul's notable coworkers include David Lawrence Rager and Matthew Perry Abrams. Their collaboration contributes to a dynamic work environment that fosters innovation and technological advancement.

Conclusion

Rahul Dilip Jagad's contributions to the field of technology through his patent and work at Oracle International Corporation highlight his role as a significant innovator. His advancements in user profile processing demonstrate the impact of specialized data structures in enhancing computational efficiency.

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