Menlo Park, CA, United States of America

Maja Kabiljo

This inventor holds 3 USPTO granted patents. Top assignee: Meta Platforms, Inc.. Active years: 2016-2019.


% Patents Active = 66.7

Average Co-Inventor Count = 3.0

ph-index = 2

Forward Citations = 85(Granted Patents)


Company Filing History:


Years Active: 2016-2019

Loading Chart...
3 patents (USPTO):Explore Patents

Title: Maja Kabiljo: Innovator in Collaborative Filtering Technologies

Introduction

Maja Kabiljo is a prominent inventor based in Menlo Park, CA (US). She has made significant contributions to the field of collaborative filtering and directed graph technologies. With a total of 3 patents, her work has advanced the way data is computed and analyzed in social networks.

Latest Patents

Maja's latest patents include innovative methods for collaborative filtering in directed graphs. One of her notable inventions focuses on predicting user behavior or interests based on the actions of other users. This system enhances computing efficiency by characterizing users as vertices in a directed graph and managing worker data across individual computers. Another patent involves striping directed graphs to efficiently perform operations on nodes, optimizing resource use and generating collective results through iterative processes.

Career Highlights

Maja Kabiljo is currently employed at Meta Platforms, Inc., where she continues to develop cutting-edge technologies. Her work has positioned her as a key player in the tech industry, particularly in the realm of social networking and data analysis.

Collaborations

Maja collaborates with talented individuals such as Deepayan Chakrabarti and Jonathan D Chang. These partnerships have fostered innovation and creativity in her projects, contributing to the success of her inventions.

Conclusion

Maja Kabiljo's contributions to collaborative filtering and directed graph technologies have made a significant impact in her field. Her innovative patents and collaborations reflect her dedication to advancing technology and improving data computation methods.

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