Redmond, WA, United States of America

Srinivas Vasu Chappidi


Average Co-Inventor Count = 3.0

ph-index = 1

Forward Citations = 8(Granted Patents)


Company Filing History:


Years Active: 2019

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1 patent (USPTO):Explore Patents

Title: Innovations by Srinivas Vasu Chappidi

Introduction

Srinivas Vasu Chappidi is an accomplished inventor based in Redmond, WA (US). He has made significant contributions to the field of data analysis and grouping through his innovative patent. His work is particularly relevant in the context of user interactions with item-specific content.

Latest Patents

Srinivas holds a patent titled "Grouping of item data using seed expansion." This patent features methods for analyzing collections of data and automatically grouping data that exhibit certain similarities. The analysis of user interactions with item-specific content can be utilized to identify groups of items that appeal to similar users. Additionally, it can help identify groups of users with demonstrated interests in similar items. The patent outlines two approaches for data analysis: a 'bottom-up' method, which discovers correlations iteratively, and a 'top-down' method, where desired top-level groups are specified at the outset. The bottom-up process can also be distributed across multiple devices or processors, enhancing efficiency when working with large data collections.

Career Highlights

Srinivas is currently employed at Amazon Technologies, Inc., where he continues to innovate and contribute to advancements in data analysis. His work has implications for improving user experience and enhancing the relevance of content presented to users.

Collaborations

Srinivas has collaborated with notable colleagues, including Gaurav Chanda and Saurabh Wadwekar. Their combined expertise fosters a creative environment that drives innovation within their projects.

Conclusion

Srinivas Vasu Chappidi's contributions to data analysis through his patent demonstrate his commitment to innovation. His work at Amazon Technologies, Inc. continues to influence how data is grouped and analyzed, ultimately enhancing user interactions with content.

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