Moscow, Russia

Viacheslav Seledkin

USPTO Granted Patents = 2 

Average Co-Inventor Count = 3.4

ph-index = 1


Company Filing History:


Years Active: 2021-2023

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2 patents (USPTO):Explore Patents

Title: Viacheslav Seledkin: Innovator in Data Anonymization and Document Clustering

Introduction

Viacheslav Seledkin is a prominent inventor based in Moscow, Russia. He has made significant contributions to the fields of data anonymization and document clustering, holding a total of 2 patents. His innovative approaches leverage advanced technologies, particularly neural networks, to address complex challenges in data processing.

Latest Patents

Seledkin's latest patents include groundbreaking methods that utilize neural networks for data anonymization. One such method involves receiving a natural language text and transforming it into a numeric representation through a neural network. This process discards the original text and enables the performance of information extraction tasks using the numeric representation. Another notable patent focuses on recursive agglomerative clustering of time-structured communications. This method represents documents as vectors based on frequency-based metrics, allowing for effective partitioning into document clusters based on their similarities.

Career Highlights

Throughout his career, Viacheslav Seledkin has worked with notable companies such as Visier Solutions, Inc. and Yva.ai, Inc. His experience in these organizations has allowed him to refine his skills and contribute to innovative projects that push the boundaries of technology.

Collaborations

Seledkin has collaborated with talented individuals in the industry, including David Yan and Victor Kuznetsov. These partnerships have fostered a creative environment that encourages the exchange of ideas and the development of cutting-edge solutions.

Conclusion

Viacheslav Seledkin stands out as an influential inventor in the realm of data processing and document management. His patents reflect a commitment to innovation and a deep understanding of complex technological challenges. Through his work, he continues to shape the future of data anonymization and clustering methodologies.

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