Company Filing History:
Years Active: 2020
Title: Subhradeep Kayal: Innovator in Funding Information Extraction
Introduction
Subhradeep Kayal is an accomplished inventor based in Amsterdam, Netherlands. He has made significant contributions to the field of natural language processing and machine learning, particularly in the extraction of funding information from text documents. His innovative approach has the potential to streamline the way funding information is identified and utilized.
Latest Patents
Subhradeep holds a patent titled "Systems and methods for extracting funder information from text." This patent describes a method that involves receiving a text document and extracting paragraphs using a natural language processing model or a machine learning model. The paragraphs are then classified as containing funding information or not. The method further includes labeling potential entities within the classified paragraphs using different named-entity recognition models. This innovative system enhances the accuracy and efficiency of extracting funding information from various text sources. He has 1 patent to his name.
Career Highlights
Subhradeep Kayal is currently employed at Elsevier, Inc., where he applies his expertise in machine learning and natural language processing. His work focuses on developing advanced systems that improve the extraction and classification of information, which is crucial for researchers and organizations seeking funding opportunities.
Collaborations
Throughout his career, Subhradeep has collaborated with notable colleagues, including Michelle Gregory and Georgios Tsatsaronis. These collaborations have fostered a productive environment for innovation and have contributed to the advancement of their shared goals in the field of information extraction.
Conclusion
Subhradeep Kayal is a pioneering inventor whose work in extracting funding information from text documents is making a significant impact in the field of natural language processing. His contributions are paving the way for more efficient methods of identifying funding opportunities, benefiting researchers and organizations alike.