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For the Inventor, By the Inventor

Bridgeport, CT, United States of America

Dilyan Kovachev

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This inventor holds 4 USPTO granted patents and 1 published patent application. Top assignee: Treasure Data, Inc.. Active years: 2024-2026.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Dilyan Kovachev. Retrieved from https://idiyas.com/inventor/dilyan-kovachev

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

USPTO Granted Patents = 4 

% Patents Active = 100.0

Average Co-Inventor Count = 2.4

ph-index = 1

Forward Citations = 1(Granted Patents)


Company Filing History:

goldMedal4 out of 12 
 
Treasure Data, Inc.
 patents

Years Active: 2024-2026

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4 patents (USPTO):Explore Patents
1. 12711158 - Interactive Adaptation of Machine Learning Models for Time Series Data (2026-08-18),
2. 12229158 - Data type-based visual profiling of large-scale database tables (2025-02-18),
3. 12061632 - Interactive adaptation of machine learning models for time series data (2024-08-13),
4. 11893038 - Data type based visual profiling of large-scale database tables (2024-02-06),

Title: Dilyan Kovachev: Innovator in Data Management and Machine Learning

Introduction

Dilyan Kovachev is a prominent inventor based in Bridgeport, Connecticut, known for his contributions to data management and machine learning technologies. With a total of three patents to his name, Kovachev has made significant strides in the field of computer-implemented methods that enhance the efficiency and effectiveness of data processing.

Latest Patents

Kovachev's latest patents include innovative methods that address complex challenges in data handling. One of his notable patents is for a "Data type-based visual profiling of large-scale database tables." This invention involves establishing programmatic connections to a large database, reading configuration files, and generating graphical visualizations to present metadata metrics effectively. Another significant patent is for the "Interactive adaptation of machine learning models for time series data." This method utilizes a HADOOP cluster and a HIVE data warehouse manager to train machine learning models, evaluate aggregated records, and produce forecasted event data visualizations.

Career Highlights

Dilyan Kovachev currently works at Treasure Data, Inc., where he applies his expertise in data management and machine learning. His work focuses on developing advanced solutions that leverage large datasets to provide actionable insights. Kovachev's innovative approaches have positioned him as a key player in the tech industry, particularly in the realm of data analytics.

Collaborations

Throughout his career, Kovachev has collaborated with talented professionals, including Gurbaksh Sharma and Pradeep Kumar Reddy Savadi. These collaborations have fostered an environment of innovation and creativity, leading to the development of cutting-edge technologies.

Conclusion

Dilyan Kovachev's contributions to data management and machine learning exemplify the impact of innovative thinking in technology. His patents reflect a commitment to advancing the field and providing valuable solutions for complex data challenges.

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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