San Jose, CA, United States of America

Harbinder Sikka

This inventor holds 3 USPTO granted patents. Top assignee: Nvidia Corporation. Active years: 2020-2023.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Harbinder Sikka. Retrieved from https://idiyas.com/inventor/harbinder-sikka

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 = 6.0

ph-index = 2

Forward Citations = 13(Granted Patents)


Company Filing History:


Years Active: 2020-2023

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3 patents (USPTO):Explore Patents

Title: Harbinder Sikka: Innovator in Deep Learning Technologies

Introduction

Harbinder Sikka is a prominent inventor based in San Jose, California. He has made significant contributions to the field of deep learning and circuit design. With a total of three patents to his name, Sikka is recognized for his innovative approaches to complex engineering challenges.

Latest Patents

One of Harbinder Sikka's latest patents focuses on deep learning-based identification of difficult-to-test nodes. This invention presents techniques to improve the accuracy and speed for detection and remediation of challenging nodes in a circuit design netlist. The methods utilize enhanced netlist representations, test point insertion, and trained neural networks to achieve these improvements.

Career Highlights

Sikka is currently employed at Nvidia Corporation, a leading technology company known for its advancements in graphics processing and artificial intelligence. His work at Nvidia has allowed him to explore and develop cutting-edge technologies that push the boundaries of what is possible in circuit design and testing.

Collaborations

Some of Harbinder Sikka's notable coworkers include Lijuan Luo and Karthikeyan Natarajan. Their collaborative efforts contribute to the innovative environment at Nvidia, fostering advancements in deep learning and circuit design.

Conclusion

Harbinder Sikka's work exemplifies the intersection of deep learning and circuit design, showcasing his commitment to innovation. His patents reflect a dedication to improving technology and solving complex engineering problems.

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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