Gaithersburg, MD, United States of America

Carl G Simon

This inventor holds 3 USPTO granted patents, plus 1 CIPO patent and 1 EPO patent. Top assignee: The United States of America, as Represented by the Secretary, Department of Health and Human Services. Active years: 2022-2026.

USPTO Granted Patents = 3

% Patents Active = 100.0

CIPO Patents = 1 (Patent Applications = 1)

EPO Patents = 1

Average Co-Inventor Count = 4.0

ph-index = 1

Forward Citations = 7(Granted Patents)

Company Filing History:

3 out of 3,688

The United States of America, as Represented by the Secretary, Department of Health and Human Services

patents

Years Active: 2022-2026

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3 patents (USPTO):Sort by Forward CitationsExplore Patents

1. 12718601 - Using machine learning and/or neural networks to validate stem cells and their derivatives (2-D cells and 3-D tissues) for use in cell therapy and tissue engineered products (2026-08-25),

2. 12020494 - Using machine learning and/or neural networks to validate stem cells and their derivatives (2-D cells and 3-D tissues) for use in cell therapy and tissue engineered products (2024-06-25),

3. 11531844 - Using machine learning and/or neural networks to validate stem cells and their derivatives (2-D cells and 3-D tissues) for use in cell therapy and tissue engineered products (2022-12-20),

Title: Innovations of Carl G Simon in Stem Cell Validation

Introduction

Carl G Simon is an accomplished inventor based in Gaithersburg, MD (US). He has made significant contributions to the field of stem cell research and validation through his innovative methods. With a total of 3 patents, Simon's work focuses on utilizing machine learning and neural networks to enhance the efficacy of cell therapy and tissue engineering.

Latest Patents

Simon’s latest patents revolve around a method for non-invasively predicting the characteristics of stem cells and their derivatives, including both 2-D cells and 3-D tissues. This method involves training a machine learning model using a variety of training cell images that represent multiple cells, along with data that identifies their characteristics. The process includes acquiring test cell images non-invasively, based on absorbance as an absolute measure of light. The trained machine learning model then predicts the characteristics of the test cells and generates release criteria for clinical preparations based on these predictions.

Career Highlights

Carl G Simon is currently affiliated with the National Institutes of Health, a component of the US Department of Health & Human Services. His work at this prestigious institution has allowed him to contribute to groundbreaking research in the field of cell therapy and tissue engineering.

Collaborations

Simon has collaborated with notable colleagues, including Kapil Bharti and Nathan A Hotaling, to advance the understanding and application of stem cell technologies.

Conclusion

Carl G Simon's innovative approaches in the validation of stem cells through machine learning are paving the way for advancements in cell therapy and tissue engineering. His contributions are vital to the ongoing research in this critical area of medicine.