Cambridge, MA, United States of America

Soundararajan Srinivasan

USPTO Granted Patents = 2 

Average Co-Inventor Count = 14.0

ph-index = 1


Company Filing History:


Years Active: 2023-2024

where 'Filed Patents' based on already Granted Patents

2 patents (USPTO):

Title: Innovations by Soundararajan Srinivasan

Introduction

Soundararajan Srinivasan is a notable inventor based in Cambridge, MA (US). He has made significant contributions to the field of machine learning, particularly in system deployments. With a total of 2 patents, his work focuses on enhancing the performance and reliability of machine learning models in production environments.

Latest Patents

One of his latest patents is titled "System and method for machine learning for system deployments without performance regressions." This invention outlines methods for ensuring that machine learning systems can be deployed without negatively impacting performance. The patent describes a performance safeguard system that designs pre-production experiments to assess the readiness of learned models. By utilizing big data processing infrastructure, it deploys a variety of learned or optimized models for query optimization. The system differentiates the impact of various query plans, selects those likely to yield significant performance improvements, and conducts experiments to observe runtime performance. Ultimately, it identifies models that promise consistent performance enhancements for deployment.

Career Highlights

Soundararajan Srinivasan is currently associated with Microsoft Technology Licensing, LLC, where he continues to innovate in the field of machine learning. His work is instrumental in developing systems that ensure safe and efficient deployment of machine learning models.

Collaborations

He collaborates with talented individuals such as Irene Rogan Shaffer and Remmelt Herbert Lieve Ammerlaan, contributing to a dynamic and innovative work environment.

Conclusion

Soundararajan Srinivasan's contributions to machine learning and system deployments are noteworthy. His patents reflect a commitment to improving the reliability and performance of machine learning applications. His work continues to influence the field and drive advancements in technology.

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