Devipriya Selvaraju

Title: Innovations by Devipriya Selvaraju

Introduction

Devipriya Selvaraju is an accomplished inventor based in Bengaluru, India. She has made significant contributions to the field of technology, particularly in image analysis and component failure prediction. With a total of three patents to her name, her work showcases the integration of machine learning in solving complex problems.

Latest Patents

One of her latest patents is titled "Image analysis for problem resolution." This method involves receiving an input of at least one image associated with an issue. The process includes extracting text from the image and determining the intent from the extracted text. Furthermore, the method recommends a response to the issue based on the determined intent, utilizing one or more machine learning models for the extracting, determining, and recommending processes.

Another notable patent is "Component failure prediction." This method retrieves operating conditions data, which includes operational details of components in a computing environment. It also gathers component replacement data and no fault found (NFF) data. The method generates mappings between operational details and replaced components, as well as between incorrectly identified components and symptoms. Using these mappings, it predicts at least one failed component based on symptoms identified in a support case.

Career Highlights

Devipriya currently works at Dell Products Inc., where she applies her innovative ideas to enhance technology solutions. Her expertise in machine learning and problem resolution has made her a valuable asset to her team.

Collaborations

Some of her coworkers include Bijan Kumar Mohanty and Karthik Sethuramalingam, with whom she collaborates on various projects to drive innovation within the company.

Conclusion

Devipriya Selvaraju's contributions to technology through her patents reflect her dedication to innovation and problem-solving. Her work continues to influence advancements in the field, showcasing the potential of machine learning in practical applications.