San Francisco, CA, United States of America

Emily A Port

This inventor holds 1 USPTO granted patent. Top assignee: International Business Machines Corporation. Active years: 2020.


Average Co-Inventor Count = 5.0

ph-index = 1


Company Filing History:


Years Active: 2020

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1 patent (USPTO):Explore Patents

Title: Emily A Port: Innovator in Data Optimization

Introduction

Emily A Port is a prominent inventor based in San Francisco, CA. She has made significant contributions to the field of data optimization, particularly in the retail sector. Her innovative approach has led to the development of a unique patent that addresses the challenges retailers face when managing large data sets.

Latest Patents

Emily holds a patent titled "Constrained large-data markdown optimizations based upon markdown budget." This patent introduces a markdown budget user interface that enables retailers to access large-scale computational resources. These resources can concurrently manipulate multi-million item data sets, allowing retailers to specify inputs such as a markdown budget constraint, store-product data sets, and a markdown objective. The system determines a markdown recommendation that satisfies both the budget constraint and the objective, providing valuable insights to retailers.

Career Highlights

Emily A Port is associated with International Business Machines Corporation (IBM), where she has been instrumental in advancing data optimization technologies. Her work has not only enhanced operational efficiency for retailers but has also paved the way for innovative solutions in data management.

Collaborations

Emily has collaborated with notable colleagues, including Jun Lei Chen and Xiao Li. These partnerships have fostered a collaborative environment that encourages the exchange of ideas and the development of cutting-edge technologies.

Conclusion

Emily A Port's contributions to data optimization through her innovative patent demonstrate her commitment to enhancing the retail industry's capabilities. Her work continues to influence how retailers manage and utilize large data sets effectively.

Profile summary based on public USPTO records.
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