Karnataka, India

Chinmay Chaturvedi

USPTO Granted Patents = 2 

Average Co-Inventor Count = 6.0

ph-index = 1

Forward Citations = 2(Granted Patents)


Company Filing History:


Years Active: 2024-2025

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2 patents (USPTO):Explore Patents

Title: Chinmay Chaturvedi: Innovator in Data Validation Technologies

Introduction

Chinmay Chaturvedi is a notable inventor based in Karnataka, India. He has made significant contributions to the field of data validation and machine learning. With a focus on enhancing the reliability of data processing systems, Chinmay has been awarded 2 patents for his innovative work.

Latest Patents

Chinmay's latest patents include groundbreaking systems and methods for data correctness and validation using validation definition language. One of his patents focuses on generating extract-transform-load (ETL) machine learning (ML) pipeline validation rules based on user input. These rules are designed to validate an ETL ML pipeline against multiple test datasets. The validation rules include compute-type validation rules for computing expected values of data structures within a dataset output by the ETL ML pipeline. Additionally, check-type validation rules are implemented to ensure that data structures within the dataset have the intended characteristics. Another patent addresses automatic expected validation definition generation for data correctness in AI/ML pipelines, further enhancing the efficiency and accuracy of data validation processes.

Career Highlights

Chinmay Chaturvedi is currently employed at Hewlett Packard Enterprise Development LP, where he continues to innovate in the field of data validation technologies. His work is instrumental in developing systems that improve the integrity of data used in machine learning applications.

Collaborations

Chinmay collaborates with talented professionals such as Chirag Talreja and Sagar Venkappa Nyamagouda, contributing to a dynamic work environment that fosters innovation and creativity.

Conclusion

Chinmay Chaturvedi's contributions to data validation and machine learning are paving the way for more reliable data processing systems. His patents reflect a commitment to enhancing the accuracy and efficiency of ETL ML pipelines.

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