Baltimore, MD, United States of America

Edward Givelberg


Average Co-Inventor Count = 2.0

ph-index = 1

Forward Citations = 1(Granted Patents)


Company Filing History:


Years Active: 2014-2016

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4 patents (USPTO):Explore Patents

Title: Edward Givelberg: Innovator in Data-Intensive Computing

Introduction

Edward Givelberg is a notable inventor based in Baltimore, MD (US). He has made significant contributions to the field of data-intensive computing, holding a total of 4 patents. His work focuses on enhancing the efficiency and functionality of data processing systems.

Latest Patents

Givelberg's latest patents include a "System and method for program and resource allocation within a data-intensive computer." This invention provides a comprehensive system for operating a data-intensive computer, which consists of a processing sub-system formed by multiple processing node servers and a database sub-system made up of several database servers. The architecture is designed to manage a collective database exceeding a petabyte of storage. Another significant patent is the "Data-intensive computer architecture," which outlines a data-intensive computer that integrates a processing sub-system and a database sub-system under a unifying operating system environment. This environment coordinates the operation of both subsystems, presenting the database as a layer in the memory hierarchy of the computer.

Career Highlights

Edward Givelberg is currently affiliated with Johns Hopkins University, where he continues to innovate in the realm of data-intensive computing. His work has been instrumental in advancing the capabilities of data processing technologies.

Collaborations

Givelberg collaborates with Sandor Szalay, contributing to the development of cutting-edge solutions in their field.

Conclusion

Edward Givelberg's contributions to data-intensive computing through his patents and work at Johns Hopkins University highlight his role as a key innovator in this rapidly evolving field. His inventions are paving the way for more efficient data processing systems.

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