Beijing, China

Yuqing Xia

This inventor holds 1 USPTO granted patent. Top assignee: Microsoft Technology Licensing, LLC. Active years: 2026.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Yuqing Xia. Retrieved from https://idiyas.com/inventor/yuqing-xia-wvoggf7c

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


Average Co-Inventor Count = 1.0

ph-index = 1


Company Filing History:


Years Active: 2026

Loading Chart...
1 patent (USPTO):Explore Patents

Title: Innovations of Yuqing Xia in Neural Network Models

Introduction

Yuqing Xia is an accomplished inventor based in Beijing, China. He has made significant contributions to the field of neural networks, particularly in the area of tensor operators. His innovative work has led to the development of a patent that enhances the efficiency of neural network models.

Latest Patents

Yuqing Xia holds a patent titled "Compiling tensor operators for neural network models based on tensor tile configurations." This patent involves systems and methods for compiling tensor operators tailored for neural network models. The process begins with receiving a tensor expression for a neural network model. Subsequently, a tensor tile configuration is determined based on specifications associated with a set of hardware devices. Finally, a set of code is generated for implementing the tensor expression, ensuring compatibility with the hardware.

Career Highlights

Yuqing Xia is currently associated with Microsoft Technology Licensing, LLC, where he continues to push the boundaries of technology. His work focuses on optimizing neural network models, which are crucial for various applications in artificial intelligence and machine learning.

Collaborations

Yuqing collaborates with talented individuals such as Jilong Xue and Lingxiao Ma, who contribute to his innovative projects and research endeavors.

Conclusion

Yuqing Xia's contributions to the field of neural networks through his patent demonstrate his expertise and commitment to advancing technology. His work not only enhances the efficiency of neural network models but also showcases the importance of collaboration in innovation.

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]
Loading…