San Ramon, CA, United States of America

David Varghese

This inventor holds 1 USPTO granted patent. Top assignee: Cadence Design Systems, Inc.. Active years: 2023.

IDiyas Innovation Intelligence. (2026). Inventor Profile: David Varghese. Retrieved from https://idiyas.com/inventor/david-varghese-ugm4ws7w

Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile


% Patents Active = 100.0

Average Co-Inventor Count = 3.0

ph-index = 1

Forward Citations = 1(Granted Patents)


Company Filing History:


Years Active: 2023

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1 patent (USPTO):Explore Patents

Title: David Varghese: Innovator in Circuit Design Technology

Introduction

David Varghese is a notable inventor based in San Ramon, California. He has made significant contributions to the field of electronic design automation (EDA) through his innovative work. His expertise lies in utilizing machine learning models to enhance circuit design processes.

Latest Patents

David Varghese holds a patent for a "Model-based simulation result predictor for circuit design." This invention provides a method for predicting simulation results for circuit designs using machine learning. It is particularly useful in measuring various aspects of circuit designs, such as timing, power, voltage, and current. The technology enables modeling simulated time measurements with minimal reliance on simulation result data.

Career Highlights

David is currently employed at Cadence Design Systems, Inc., a leading company in the EDA industry. His work focuses on improving the efficiency and accuracy of circuit design processes. With one patent to his name, he has established himself as an innovator in his field.

Collaborations

David collaborates with talented professionals, including Saleha Khatun and Roland Ruehl. Their combined expertise contributes to the advancement of technology in circuit design.

Conclusion

David Varghese is a pioneering inventor whose work in circuit design technology showcases the potential of machine learning in electronic design automation. His contributions are paving the way for more efficient and effective circuit design processes.

Profile summary based on public USPTO records.
Data Sources: USPTO Patent Grant XML, Patent Center, EPO & CIPO • Normalized by IDiyas Innovation Graph. Methodology & provenance architecturePlease report any incorrect information to [email protected]
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