Pittsburgh, PA, United States of America

Adilakshmi Veerubhotla


Average Co-Inventor Count = 5.0

ph-index = 1

Forward Citations = 1(Granted Patents)


Company Filing History:


Years Active: 2021

where 'Filed Patents' based on already Granted Patents

1 patent (USPTO):

Title: Adilakshmi Veerubhotla: Innovator in Natural Language Processing

Introduction

Adilakshmi Veerubhotla is a notable inventor based in Pittsburgh, PA (US). He has made significant contributions to the field of natural language processing, particularly in document summarization techniques. His innovative approach utilizes hyperbolic embeddings to enhance the efficiency and accuracy of summarizing natural language documents.

Latest Patents

Veerubhotla holds a patent for "Natural language document summarization using hyperbolic embeddings." This patent describes a mechanism that implements a summarization process for natural language documents. The mechanism responds to user queries by producing a hyperbolic embedding model of the query. It compares the embeddings of the query to those associated with sentences in the document. By identifying sentences that have semantic specificity to the query, the mechanism adds these sentences to the summary and outputs the final summary to the user. This innovative approach significantly improves the summarization process.

Career Highlights

Adilakshmi Veerubhotla is currently employed at International Business Machines Corporation, commonly known as IBM. His work at IBM focuses on advancing technologies in natural language processing and artificial intelligence. His contributions have been instrumental in developing more effective communication tools and enhancing user experiences.

Collaborations

Veerubhotla has collaborated with several talented individuals in his field, including Anastas Stoyanovsky and Steven Michael Pritko. These collaborations have fostered a creative environment that encourages innovation and the sharing of ideas.

Conclusion

Adilakshmi Veerubhotla is a pioneering inventor whose work in natural language processing is shaping the future of document summarization. His patent on hyperbolic embeddings showcases his commitment to advancing technology and improving user interactions with natural language documents.

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