Musashino, Japan

Takumi Fukami

This inventor holds 1 USPTO granted patent and 10 published patent applications. Top assignee: Ntt Corporation. Active years: 2026.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Takumi Fukami. Retrieved from https://idiyas.com/inventor/takumi-fukami

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

USPTO Granted Patents = 1 

% Patents Active = 100.0

Average Co-Inventor Count = 3.0

ph-index = 1


Company Filing History:


Years Active: 2026

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1 patent (USPTO):Explore Patents

Title: Takumi Fukami and Distributed Learning Innovation.

Introduction

Takumi Fukami is an inventor associated with NTT Corporation in Musashino, Japan. His patent work addresses distributed machine learning, with a focus on accelerating model convergence while maintaining security.

Latest Patents

Fukami is associated with 1 patent: “Distributed Learning Method, Distributed Learning System, Server, and Program.” The invention describes a process in which client devices train models using their learning data, while a server aggregates the client models into a global model according to a predetermined formula. The server checks whether an end condition has been met. If it has, learning ends with the current global model; otherwise, the server sends that model to the clients to initialize the next learning cycle.

Career Highlights

Fukami’s listed patent reflects work on distributed learning systems that coordinate model training between clients and a server. The approach combines iterative model updates and server-side aggregation to support convergence while addressing security.

Collaborations

Dai Ikarashi and Iifan Tyou are identified as Fukami’s coworkers. The available information does not specify their roles in the patent or whether they collaborated directly on the invention.

Conclusion

Takumi Fukami’s patent contribution centers on a distributed learning method that coordinates client training and server aggregation to advance secure, efficient model convergence.

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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