L'Isle Jourdain Gers, France

Douglas Mclelland

This inventor holds 1 USPTO granted patent. Top assignee: Brainchip, Inc.. Active years: 2026.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Douglas Mclelland. Retrieved from https://idiyas.com/inventor/douglas-mclelland-2tp9enf5

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 = 4.0

ph-index = 1


Company Filing History:


Years Active: 2026

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1 patent (USPTO):Explore Patents

Title: Douglas Mclelland: Innovator in Spiking Neural Networks

Introduction

Douglas Mclelland is a prominent inventor based in L'Isle Jourdain Gers, France. He has made significant contributions to the field of artificial intelligence, particularly in the development of spiking neural networks. His innovative work focuses on enhancing the capabilities of neural networks to learn from various types of datasets.

Latest Patents

Mclelland holds a patent for an improved spiking neural network. This patent outlines a system, method, and computer program designed to facilitate unsupervised, semi-supervised, and supervised extraction of features from input datasets. The invention involves modifying a base neural network with supplementary spiking neurons to enhance its learning capabilities.

Career Highlights

Douglas Mclelland is currently associated with Brainchip, Inc., where he continues to push the boundaries of neural network technology. His work has been instrumental in advancing the understanding and application of spiking neural networks in various fields.

Collaborations

Mclelland collaborates with notable colleagues, including Milind Joshi and Kristofor D Carlson. Their combined expertise contributes to the innovative projects at Brainchip, Inc.

Conclusion

Douglas Mclelland's contributions to the field of spiking neural networks exemplify the potential of innovative technologies in artificial intelligence. His work continues to inspire advancements in machine learning and neural network applications.

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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