Plano, TX, United States of America

Abhishek Sanghavi

USPTO Granted Patents = 3 

Average Co-Inventor Count = 5.6

ph-index = 2

Forward Citations = 13(Granted Patents)


Location History:

  • Plano, TX (US) (2020)
  • Dallas, TX (US) (2022 - 2023)

Company Filing History:


Years Active: 2020-2023

where 'Filed Patents' based on already Granted Patents

3 patents (USPTO):

Title: Abhishek Sanghavi: Innovator in Machine Learning and Document Processing

Introduction

Abhishek Sanghavi is a notable inventor based in Plano, TX (US). He has made significant contributions to the field of artificial intelligence and machine learning, particularly in the area of document processing. With a total of three patents to his name, Sanghavi is recognized for his innovative approaches to information extraction.

Latest Patents

Sanghavi's latest patents include a continuous machine learning method and system for information extraction. This invention describes methods and systems for AI-assisted document annotation and training of machine learning-based models for document data extraction. The continuous machine learning approach creates document processing pipelines that ensure accurate and efficient data extraction from various types of documents, including structured, semi-structured, and unstructured text.

Career Highlights

Abhishek Sanghavi is currently employed at Pricewaterhousecoopers LLP, where he applies his expertise in machine learning and AI. His work focuses on enhancing document processing capabilities, which is crucial for organizations that rely on accurate data extraction from large volumes of documents.

Collaborations

Some of his notable coworkers include Joseph G Harrington and Jacob T Wilson. Their collaboration contributes to the innovative environment at Pricewaterhousecoopers LLP, fostering advancements in technology and document processing.

Conclusion

Abhishek Sanghavi stands out as an inventor who is pushing the boundaries of machine learning and document processing. His contributions are paving the way for more efficient data extraction methods in various industries.

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