Moscow, Russia

Ilia Federov

This inventor holds 1 USPTO granted patent. Top assignee: Nvidia Corporation. Active years: 2026.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Ilia Federov. Retrieved from https://idiyas.com/inventor/ilia-federov

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

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1 patent (USPTO):Explore Patents

Title: Ilia Federov: Innovator in Emotion Recognition Technology

Introduction

Ilia Federov is a prominent inventor based in Moscow, Russia. He has made significant contributions to the field of emotion recognition through his innovative patent. His work focuses on utilizing deep learning techniques to infer emotions from audio data, showcasing the intersection of technology and human emotion.

Latest Patents

Ilia Federov holds a patent titled "Inferring emotion from speech in audio data using deep learning." This patent describes a deep neural network that can be trained to infer emotion data from input audio. The network is designed to be transformer-based, capable of inferring probability values for a set of emotions or emotion classes. The emotion probability values can be adjusted using various heuristics, allowing for the smoothing of emotion determinations over time. Additionally, users can modify these determinations through an interface, blending prior emotion values with the current determinations. The determined emotion values can then be utilized in emotion-based operations, such as audio-driven speech animation.

Career Highlights

Ilia Federov is currently associated with Nvidia Corporation, a leading technology company known for its advancements in graphics processing and artificial intelligence. His role at Nvidia allows him to work on cutting-edge projects that leverage deep learning and emotion recognition technologies.

Collaborations

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Conclusion

Ilia Federov's innovative work in emotion recognition technology exemplifies the potential of deep learning in understanding human emotions through audio data. His contributions are paving the way for advancements in various applications, including speech animation and user interaction.

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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