Michael Yiupun Kwong

Title: Michael Yiupun Kwong: Innovator in Document Entity Extraction

Introduction

Michael Yiupun Kwong is an accomplished inventor based in Mountain View, CA. He has made significant contributions to the field of document entity extraction through his innovative patent. His work focuses on utilizing machine-learned models to enhance the efficiency and accuracy of data extraction from documents.

Latest Patents

Michael holds a patent titled "Document entity extraction using machine-learned models." This patent describes systems and methods for performing document entity extraction. The method includes receiving an inference document and a target schema, generating document and schema inputs, and obtaining extraction inputs based on combinations of these inputs. The process involves providing these inputs to a machine-learned model and validating the extracted entity data based on reference and inference spatial locations.

Career Highlights

Michael is currently employed at Google Inc., where he applies his expertise in machine learning and data extraction. His innovative approach has led to advancements in how documents are processed and analyzed, making significant impacts in various applications.

Collaborations

Some of Michael's notable coworkers include Jiaqi Mu and Florian Luisier. Their collaborative efforts contribute to the innovative environment at Google Inc., fostering advancements in technology and research.

Conclusion

Michael Yiupun Kwong is a notable inventor whose work in document entity extraction showcases the potential of machine learning in improving data processing. His contributions continue to influence the field and inspire future innovations.