Mountain View, CA, United States of America

Mariana Sharp


Average Co-Inventor Count = 7.0

ph-index = 1


Company Filing History:


Years Active: 2021-2023

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2 patents (USPTO):

Title: Innovator Spotlight: Mariana Sharp

Introduction

Mariana Sharp, based in Mountain View, CA, is a noteworthy inventor recognized for her contributions in the realm of data processing frameworks. With two patents to her name, she is making significant strides in innovation that optimize system performance.

Latest Patents

One of Mariana's latest patents involves a "System for automatically evaluating a change in a large population of processing jobs." This groundbreaking invention focuses on assessing the rollout of changes within a data processing framework (DPF). The process begins by selecting a first set of jobs from a larger pool, with the selected jobs processed using the proposed changes, while the remainder operates without those modifications. Through this systematic evaluation, performance cost values are determined for each job, allowing for a comprehensive assessment to establish whether the proposed changes yield beneficial results for the DPF.

Career Highlights

Currently employed at Google Inc., Mariana has established herself as a pivotal figure in her field. Her work has significant implications for improving data processing efficiency and reducing operational costs in computing environments. Her innovative approaches and technical expertise have positioned her at the forefront of technology development.

Collaborations

Throughout her career, Mariana has collaborated with talented individuals such as Craig D. Chambers and Jelena Pjesivac-Grbovic. These partnerships reflect her ability to work within multidisciplinary teams, further enhancing the scope and impact of her inventions.

Conclusion

Mariana Sharp's inventive spirit and commitment to innovation have resulted in valuable advancements in data processing technologies. With her two patents, she continues to contribute to the evolving landscape of technology, promising a future where processing efficiency is significantly enhanced through her work.

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