Vancouver, Canada

Atilim Cetin


Average Co-Inventor Count = 6.6

ph-index = 3

Forward Citations = 17(Granted Patents)


Company Filing History:


Years Active: 2020-2022

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3 patents (USPTO):

Title: Atilim Cetin: Innovator in Distributed Database Technologies

Introduction

Atilim Cetin is a prominent inventor based in Vancouver, Canada. He has made significant contributions to the field of distributed databases, holding a total of 3 patents. His work focuses on enhancing data management and storage techniques, which are crucial in today's data-driven world.

Latest Patents

Cetin's latest patents include innovative methods for partition splitting in distributed databases. This patent describes a system where a partition of data is divided into sub-partitions, allowing for more efficient data management. The first portion of the data is assigned to one sub-partition, while the second portion is assigned to another. This method ensures that the partition does not receive new data after it has been split, optimizing data handling.

Another notable patent is for dynamic distributed data clustering using multi-level hash trees. This technique involves clustering data at the point of ingestion, utilizing a multi-level hash tree (MLHT)-based index. The MLHT maps a hierarchy of attribute values to physical storage resources, allowing for scalable and efficient data storage solutions.

Career Highlights

Atilim Cetin is currently employed at Amazon Technologies, Inc., where he continues to develop innovative solutions in data management. His expertise in distributed databases has positioned him as a valuable asset in the tech industry.

Collaborations

Cetin has collaborated with notable colleagues, including Sandeep Bhatia and Timothy Andrew Rath. These partnerships have fostered a creative environment that encourages the development of cutting-edge technologies.

Conclusion

Atilim Cetin's contributions to distributed database technologies exemplify his commitment to innovation. His patents reflect a deep understanding of data management challenges and offer practical solutions for the future.

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