Seattle, WA, United States of America

Emine Busra Celikkaya


Average Co-Inventor Count = 7.3

ph-index = 2

Forward Citations = 10(Granted Patents)


Company Filing History:


Years Active: 2022-2025

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3 patents (USPTO):

Title: Emine Busra Celikkaya: Innovator in Ontology Linking

Introduction

Emine Busra Celikkaya is a prominent inventor based in Seattle, WA. She has made significant contributions to the field of ontology linking, with a focus on unstructured text. With a total of 3 patents to her name, her work is paving the way for advancements in machine learning and data processing.

Latest Patents

One of her latest patents is titled "Service architecture for ontology linking of unstructured text." This patent describes techniques for linking unstructured text to a standardized ontology. The service architecture allows for the segmentation and tokenization of unstructured text, which is then processed by multiple deep machine learning models. These models are trained to identify specific entities and relationships between them. The service performs a search of the standardized ontology to find similar candidates for the detected entities and ranks them based on their similarity. The output includes a result identifying the highest-ranked candidate from the standardized ontology.

Career Highlights

Emine is currently employed at Amazon Technologies, Inc., where she continues to innovate and develop her ideas. Her work is instrumental in enhancing the capabilities of machine learning applications, particularly in the realm of natural language processing.

Collaborations

Emine has collaborated with notable colleagues, including Thiruvarul Selvan Senthivel and Parminder Bhatia. These collaborations have further enriched her research and development efforts.

Conclusion

Emine Busra Celikkaya is a trailblazer in the field of ontology linking, with her innovative patents contributing to the advancement of technology. Her work at Amazon Technologies, Inc. exemplifies her commitment to pushing the boundaries of what is possible in machine learning and data processing.

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