Mill Creek, WA, United States of America

Deep Sharma

This inventor holds 1 USPTO granted patent. Top assignee: Amazon Technologies, Inc.. Active years: 2026.


Average Co-Inventor Count = 1.0


Company Filing History:


Years Active: 2026

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1 patent (USPTO):Explore Patents

Title: Deep Sharma - Innovator in Product Recommendation Systems

Introduction

Deep Sharma is a notable inventor based in Mill Creek, WA (US). He has made significant contributions to the field of product recommendation systems, particularly through his innovative patent that focuses on identifying trends and matching products accordingly.

Latest Patents

Deep Sharma holds a patent for a system and method that provides product recommendations based on detected trends. This patent outlines a process for determining trends from product information by analyzing product types and attribute groupings, as well as utilizing time series data. The system performs textual and visual similarity matching between trends and products, allowing for a calculated score for each product based on its relevance to identified trends and user activity. The scored products can then be presented to users for purchase, categorized by trend or general trend categories. This innovative approach enhances the shopping experience by aligning product offerings with current market trends.

Career Highlights

Deep Sharma is currently employed at Amazon Technologies, Inc., where he continues to develop and refine his innovative ideas. His work at Amazon has allowed him to leverage cutting-edge technology and data analysis to improve product recommendation systems.

Collaborations

Deep has collaborated with talented coworkers, including Mani Bhar and Amy Ruschak, who contribute to the development of advanced technologies in the field.

Conclusion

Deep Sharma's contributions to product recommendation systems exemplify the intersection of technology and consumer behavior. His innovative patent and work at Amazon Technologies, Inc. highlight his role as a key player in enhancing the shopping experience through trend-based product recommendations.

Profile summary based on public USPTO records.
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