Poznan, Poland

Pawel Marcin Liskowski

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

IDiyas Innovation Intelligence. (2026). Inventor Profile: Pawel Marcin Liskowski. Retrieved from https://idiyas.com/inventor/pawel-marcin-liskowski

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


Company Filing History:


Years Active: 2026

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1 patent (USPTO):Explore Patents

Title: Pawel Marcin Liskowski: Innovator in AI Model-Based Data Filtering

Introduction

Pawel Marcin Liskowski is a notable inventor based in Poznan, Poland. He has made significant contributions to the field of artificial intelligence, particularly in data filtering technologies. His innovative approach leverages AI model cascades to enhance data processing efficiency.

Latest Patents

Liskowski holds a patent for a "Cascade AI model-based data filtering based on prompt." This invention provides systems, methods, and devices that utilize AI model cascades to filter data within a database system based on user-provided prompts. The technology optimizes data filtering operations while balancing computational costs and accuracy, making it particularly useful for large-scale data queries. He has 1 patent to his name.

Career Highlights

Liskowski is currently employed at Snowflake Inc., a company renowned for its cloud-based data warehousing solutions. His work focuses on integrating advanced AI techniques into data management systems, contributing to the company's innovative offerings in the tech industry.

Collaborations

Throughout his career, Liskowski has collaborated with talented professionals, including Paritosh Aggarwal and Bowei Chen. These collaborations have fostered a creative environment that encourages the development of cutting-edge technologies.

Conclusion

Pawel Marcin Liskowski is a prominent figure in the realm of artificial intelligence and data filtering. His contributions through innovative patents and collaborations continue to shape the future of data processing technologies.

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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