Boston, MA, United States of America

Andrei Lougovtsov

This inventor holds 1 USPTO granted patent and 2 published patent applications. Top assignee: Ocient Holdings LLC. Active years: 2026.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Andrei Lougovtsov. Retrieved from https://idiyas.com/inventor/andrei-lougovtsov

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

USPTO Granted Patents = 1 

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: Andrei Lougovtsov and Database-System Innovation.

Introduction

Andrei Lougovtsov is an inventor associated with Ocient Holdings LLC in Boston, Massachusetts. His patent work concerns integrating machine-learning models into database-system configuration and query processing.

Latest Patents

The provided information identifies one patent associated with Lougovtsov: “Updating System Configuration Data to Include Objects for Machine Learning Models in a Database System.” The invention describes generating a machine-learning model from a training set of database rows using multiple operators, then updating system configuration data to track the model as an object. A subsequent query can use that configuration information to apply the model to a set of rows according to the object’s properties. The supplied data lists 1 patent and does not specify a filing or grant date.

Career Highlights

Lougovtsov’s listed work at Ocient Holdings LLC focuses on database systems and machine learning. The described invention connects model generation, system configuration, and query execution within a database environment.

Collaborations

The provided information names Jason Arnold and Kevin Garner as Lougovtsov’s coworkers. It does not specify their roles in the patent or whether they collaborated on the invention.

Conclusion

Andrei Lougovtsov’s identified patent addresses how database systems can track and apply machine-learning models through configuration data, reflecting his work in database and machine-learning technology.

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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