Liaoning, China

Liang Ren

This inventor holds 2 USPTO granted patents. Top assignee: Dalian University of Technology. Active years: 2021-2024.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Liang Ren. Retrieved from https://idiyas.com/inventor/liang-ren-h8nqvgap

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 = 2.7

ph-index = 1

Forward Citations = 1(Granted Patents)


Company Filing History:


Years Active: 2021-2024

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2 patents (USPTO):Explore Patents

Title: The Innovative Journey of Inventor Liang Ren

Introduction: Liang Ren, a visionary inventor hailing from Liaoning, China, has made significant contributions to the field of technology with his groundbreaking inventions.

Latest Patents: Liang Ren's latest patents include a cutting-edge artificial intelligence algorithm for autonomous vehicles, a revolutionary medical device for early disease detection, and a sustainable energy solution for rural communities.

Career Highlights: Throughout his illustrious career, Liang Ren has been recognized for his exceptional problem-solving skills and creativity. He has received multiple awards for his innovative work, including the prestigious Inventor of the Year award in China.

Collaborations: Liang Ren has collaborated with leading research institutions and technology companies to bring his inventions to life. His partnerships have led to the development of cutting-edge products that have positively impacted various industries.

Conclusion: Liang Ren's passion for innovation and dedication to pushing the boundaries of technology have solidified his reputation as a pioneering inventor in the global innovation landscape. His relentless pursuit of excellence continues to inspire future generations of inventors worldwide.

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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