Rajashree Chandrashekar

Title: Innovations by Rajashree Chandrashekar

Introduction

Rajashree Chandrashekar is an accomplished inventor based in Bengaluru, India. She has made significant contributions to the field of technology, particularly in the area of decision logic and machine learning. With a total of three patents to her name, her work is recognized for its innovative approach to solving complex problems.

Latest Patents

One of her latest patents is a "Decision logic translation system and method." This automated system converts legacy decision logic into a target format. The system receives legacy files and outputs business rule content in a standard rule structure, according to the selected target format. This process involves decision logic-based rule extraction, addressing the challenges of incomplete rule extraction and the massive manual effort typically required for verification.

Another notable patent involves utilizing machine learning models for identifying a subject of a query, a context for the subject, and a workflow. In this implementation, a device receives a query from a user and processes it alongside data from an enterprise system. The device identifies the subject and context of the query, determining a workflow and key performance indicators associated with the products or services offered. This information is then provided to the user via a virtual assistant or user interface.

Career Highlights

Rajashree currently works at Accenture Global Solutions Limited, where she applies her expertise in technology and innovation. Her work has been instrumental in developing systems that enhance business processes and improve efficiency.

Collaborations

Some of her notable coworkers include Gopali Raval Contractor and Raghuram Yaddanapudi, who contribute to the collaborative environment at Accenture.

Conclusion

Rajashree Chandrashekar's innovative patents and contributions to technology demonstrate her commitment to advancing the field. Her work not only addresses existing challenges but also paves the way for future developments in decision logic and machine learning.