CA

Dave Aime Desire Kodjo


Average Co-Inventor Count = 5.3

ph-index = 1


Location History:

  • Quebec, CA (2020)
  • Sainte-Marthe-sur-le-Lac, CA (2020)

Company Filing History:


Years Active: 2020

where 'Filed Patents' based on already Granted Patents

2 patents (USPTO):

Title: Innovations by Dave Aime Desire Kodjo

Introduction

Dave Aime Desire Kodjo is an accomplished inventor based in California. He has made significant contributions to the field of information lifecycle management and data storage solutions. With a total of 2 patents, his work focuses on enhancing the efficiency of data management systems.

Latest Patents

Kodjo's latest patents include "Dynamic policy prioritization and translation of business rules into actions against storage volumes" and "Data compression determination for storage area networks." The first patent describes a computer-implemented method that involves reading business rules and policies for managing data in storage environments. It emphasizes the importance of analyzing available storage and capacity, dynamically prioritizing policies, and executing actions based on these priorities. The second patent outlines a method for determining whether data compression should occur at different layers within a storage area network. It assesses data volume and makes decisions on compression based on specific metrics.

Career Highlights

Kodjo is currently employed at International Business Machines Corporation (IBM), where he continues to innovate in the field of data management. His work has been instrumental in developing advanced solutions that address the complexities of data storage and retrieval.

Collaborations

Some of his notable coworkers include John Jason Auvenshine and Laura A Richardson. Their collaborative efforts contribute to the innovative environment at IBM.

Conclusion

Dave Aime Desire Kodjo's contributions to the field of data management through his patents and work at IBM highlight his role as a key innovator in the industry. His advancements in information lifecycle management and data compression techniques are paving the way for more efficient data storage solutions.

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