Beijing, China

Lidong Zhou

This inventor holds 2 USPTO granted patents and 3 published patent applications and 1 EPO patent. Top assignee: Microsoft Technology Licensing, LLC. Active years: 2026.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Lidong Zhou. Retrieved from https://idiyas.com/inventor/lidong-zhou-olzo8714

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

Calculating rank
USPTO Granted Patents = 2 

 

Average Co-Inventor Count = 7.0

ph-index = 1


Company Filing History:


Years Active: 2026

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2 patents (USPTO):Explore Patents

Title: Lidong Zhou - Innovator in Neural Network Technologies

Introduction: Lidong Zhou is an accomplished inventor based in Beijing, China. He is currently associated with Microsoft Technology Licensing, LLC. With a focus on advancing neural network technologies, Lidong has made significant contributions to the field through his innovative patent applications.

Latest Patent Applications: Lidong Zhou has filed several notable patent applications, including:

1. **Performing Dynamic Sparse Computation on Dense Computation-Efficient Computing Devices**: This application describes techniques for processing dynamically sparse neural networks as dense computations. It involves translating an input tensor from a sparse format into a dense format, allowing for efficient dense computation. The output data can then be converted back into the sparse format through a reverse permutation.

2. **Parallelization Plan Generation for a Neural Network**: This application outlines methods for designing and generating a parallelization plan for neural networks. It enables the distribution of workloads across multiple devices by transforming operators and tensors into functionally equivalent forms, which are then scheduled for execution on separate devices.

Conclusion: Lidong Zhou's work in the realm of neural networks showcases his innovative spirit and dedication to advancing technology. His contributions through patent applications reflect his commitment to enhancing computational efficiency in complex systems.

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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