Mountain View, CA, United States of America

Sricharan Kallur Palli Kumar

USPTO Granted Patents = 18 


Average Co-Inventor Count = 4.4

ph-index = 2

Forward Citations = 12(Granted Patents)


Location History:

  • Mountain View, CA (US) (2021 - 2024)
  • Fremont, CA (US) (2023 - 2024)

Company Filing History:


Years Active: 2021-2025

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18 patents (USPTO):Explore Patents

Title: Innovations of Sricharan Kallur Palli Kumar

Introduction

Sricharan Kallur Palli Kumar is a prominent inventor based in Mountain View, California. He has made significant contributions to the field of machine learning and image manipulation, holding a total of 18 patents. His work focuses on developing advanced systems that enhance the accuracy and efficiency of machine learning models.

Latest Patents

Among his latest patents is a "Machine learning model-agnostic confidence calibration system and method." This innovative method involves extracting key-value pairs from documents, classifying match probabilities, and generating calibrated confidence scores to improve decision-making in machine learning applications. Another notable patent is "Augmented diffusion inversion using latent trajectory optimization." This patent describes a process that utilizes augmented denoising diffusion implicit models for image generation and manipulation, correcting inherent biases to produce more accurate and responsive outputs.

Career Highlights

Sricharan currently works at Intuit, Inc., where he applies his expertise in machine learning to develop cutting-edge technologies. His contributions have been instrumental in advancing the capabilities of the company's products and services.

Collaborations

He has collaborated with notable coworkers, including Cynthia Joann Osmon and Roger Charles Meike, to further enhance the innovative projects at Intuit.

Conclusion

Sricharan Kallur Palli Kumar's work exemplifies the intersection of technology and innovation, particularly in machine learning and image processing. His patents reflect a commitment to improving the accuracy and functionality of modern systems.

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