Seattle, WA, United States of America

Paul H Kang

This inventor holds 1 USPTO granted patent. Top assignee: Amazon Technologies, Inc.. Active years: 2021.


% Patents Active = 100.0

Average Co-Inventor Count = 5.0

ph-index = 1

Forward Citations = 12(Granted Patents)


Company Filing History:


Years Active: 2021

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1 patent (USPTO):Explore Patents

Title: Paul H Kang: Innovator in Synthetic Document Generation

Introduction: Paul H Kang is a notable inventor based in Seattle, WA (US). He has made significant contributions to the field of synthetic document generation, showcasing his innovative spirit and technical expertise. His work is particularly relevant in the context of machine learning and document analysis.

Latest Patents: Paul H Kang holds 1 patent for a synthetic document generator. This invention is designed to obtain a configuration for a synthetic document derived from real-world documents. The configuration specifies element templates to be included in the synthetic document and weights for these templates. The system generates synthetic documents based on this configuration, producing diversified versions of the specified element templates. Additionally, annotation documents are created to provide information describing the respective synthetic documents. A machine learning model can be trained using these synthetic and annotation documents, allowing for continuous improvement through feedback from the analysis of real-world documents.

Career Highlights: Paul H Kang is currently employed at Amazon Technologies, Inc., where he applies his skills in developing innovative solutions. His work at Amazon reflects his commitment to advancing technology and improving processes through his inventions.

Collaborations: Some of his notable coworkers include Amulya Srivastava and Vivek Bhadauria, who contribute to the collaborative environment that fosters innovation at Amazon.

Conclusion: Paul H Kang's contributions to synthetic document generation highlight his role as an inventor in the tech industry. His innovative approach not only enhances document analysis but also supports the development of machine learning models.

Profile summary based on public USPTO records.
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