Mountain View, CA, United States of America

Shubha Umesh Nabar

USPTO Granted Patents = 11 

Average Co-Inventor Count = 5.3

ph-index = 4

Forward Citations = 204(Granted Patents)


Location History:

  • Stanford, CA (US) (2010)
  • Mountain View, CA (US) (2013 - 2016)
  • Sunnyvale, CA (US) (2017 - 2024)

Company Filing History:


Years Active: 2010-2025

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11 patents (USPTO):Explore Patents

Title: Shubha Umesh Nabar: Innovator in Machine Learning and Recommendations

Introduction

Shubha Umesh Nabar is a prominent inventor based in Mountain View, CA, known for his significant contributions to the fields of machine learning and recommendation systems. With a total of 11 patents to his name, Nabar has made strides in enhancing the performance and usability of machine learning technologies.

Latest Patents

Nabar's latest patents include innovative methods for automatic generation of explanations based on data lineage and user feedback. This patent focuses on improving the performance of machine learning systems by modifying training data in response to user feedback. Another notable patent is for a multi-tenant, metadata-driven recommendation system, which involves generating models for recommendations by embedding target and item data sets in a shared coordinate space. These advancements showcase his commitment to refining machine learning applications for better decision-making.

Career Highlights

Throughout his career, Nabar has worked with leading technology companies, including Microsoft Technology Licensing, LLC and Salesforce, Inc. His experience in these organizations has allowed him to collaborate on cutting-edge projects that push the boundaries of technology.

Collaborations

Some of his notable coworkers include Michael Ching and Leah McGuire, who have contributed to his innovative projects and research endeavors.

Conclusion

Shubha Umesh Nabar's work in machine learning and recommendation systems exemplifies the impact of innovation in technology. His patents and career achievements reflect a dedication to advancing the field and improving user experiences.

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