Vancouver, Canada

Soroush Radpour

This inventor holds 2 USPTO granted patents. Top assignee: Google Inc.. Active years: 2024-2026.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Soroush Radpour. Retrieved from https://idiyas.com/inventor/soroush-radpour

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


% Patents Active = 50.0

Average Co-Inventor Count = 2.0

ph-index = 1


Company Filing History:


Years Active: 2024-2026

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2 patents (USPTO):Explore Patents

Title: Soroush Radpour: Innovator in Data Processing Systems

Introduction

Soroush Radpour is a notable inventor based in Vancouver, Canada. He has made significant contributions to the field of data processing systems, particularly in the area of distributed training.

Latest Patents

Soroush holds a patent for a "Reduction server for fast distributed training." This innovative data processing system includes one or more host processing devices that support the instantiation of multiple virtual machines. A first set of virtual machines runs worker processes, each operating on a respective data set to produce a gradient. The system also includes a second set of virtual machines running reducer processes that aggregate the gradients produced by the worker processes. The aggregated gradient is then broadcasted to each worker process, enhancing the efficiency of distributed training.

Career Highlights

Soroush Radpour is currently employed at Google Inc., where he continues to develop cutting-edge technologies in data processing. His work has been instrumental in advancing the capabilities of distributed systems.

Collaborations

Soroush collaborates with Chang Lan, contributing to innovative projects that push the boundaries of technology.

Conclusion

Soroush Radpour's contributions to data processing systems exemplify the impact of innovative thinking in technology. His patent and work at Google Inc. highlight his role as a key player in the field of distributed training.

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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