Fremont, CA, United States of America

Sreeji Krishnan Das

USPTO Granted Patents = 15 

Average Co-Inventor Count = 4.9

ph-index = 4

Forward Citations = 110(Granted Patents)


Location History:

  • Foster City, CA (US) (2012)
  • Fremont, CA (US) (2019 - 2024)

Company Filing History:


Years Active: 2012-2025

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15 patents (USPTO):

Title: Innovations of Sreeji Krishnan Das

Introduction

Sreeji Krishnan Das is a prominent inventor based in Fremont, CA. He has made significant contributions to the field of analytics and machine learning, holding a total of 15 patents. His work focuses on enhancing the efficiency and effectiveness of data analysis through innovative techniques.

Latest Patents

Sreeji's latest patents include "Automatically-generated labels for time series data and numerical lists to use in analytic and machine learning systems." This patent discloses techniques for performing analytics using automatically generated labels for time series data and numerical lists. The system loads a set of time series datasets, assigns descriptive labels to data points, and identifies patterns indicative of events affecting computing resources. Another notable patent is related to "identifying process flows from log files and visualizing the flow." This patent involves generating visual representations of identified process flows and clustering tree structures based on their shape using hashing algorithms.

Career Highlights

Sreeji currently works at Oracle International Corporation, where he applies his expertise in analytics and machine learning. His innovative approaches have contributed to the development of advanced systems that improve data processing and visualization.

Collaborations

Sreeji collaborates with talented individuals such as Jae Young Yoon and Dhileeban Kumaresan, enhancing the collective knowledge and innovation within his team.

Conclusion

Sreeji Krishnan Das is a distinguished inventor whose work in analytics and machine learning has led to significant advancements in the field. His contributions continue to shape the future of data analysis and visualization.

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