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For the Inventor, By the Inventor

Toronto, Canada

Naval Shah

This inventor holds 17 USPTO granted patents and 42 published patent applications. Top assignee: Maplebear Inc.. Active years: 2025-2026.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Naval Shah. Retrieved from https://idiyas.com/inventor/naval-shah

Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile

USPTO Granted Patents = 17 

% Patents Active = 17.6

Average Co-Inventor Count = 4.1

ph-index = 1


Company Filing History:

goldMedal17 out of 349 
 
Maplebear Inc.
 patents

Years Active: 2025-2026

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17 patents (USPTO):Explore Patents
1. 12755313 - Using a trained machine-learning model to facilitate picking items in a warehouse (2026-10-06),
2. 12749091 - Artificial intelligence agent for personalized communication with users of an online system (2026-09-29),
3. 12749047 - Automated identification of items placed in a cart and routing based on same (2026-09-29),
4. 12675816 - Using a machine learning model to predict a user's quantity ceiling for different categories of items in a catalog (2026-07-07),
5. 12675381 - Device error priority assignment generation for smart cart systems (2026-07-07),
6. 12664524 - Smart cart issue prediction with remedial workflow (2026-06-23),
7. 12650890 - Using trained machine-learning model to detect errors based on interactions of users of an online system with physical devices (2026-06-09),
8. 12646032 - Using a trained machine-learning model of an online system to handle unclaimed online pickup orders (2026-06-02),
9. 12632504 - Ranking search results based on user intent for recipe ingredients (2026-05-19),
10. 12614223 - Dynamic determination of event type using multitask classification model for increasing efficiency of item pipeline (2026-04-28),
11. 12614222 - Using a trained model to generate action recommendations by predicting metrics related to items ordered at an online system (2026-04-28),
12. 12608674 - Machine learning model for predicting scheduled delivery for a self-picked order (2026-04-21),
13. 12579499 - Predicting whether temperature-sensitive items will transition outside of a target temperature range during transport using a machine learning model (2026-03-17),
14. 12572552 - Using machine-learning model of an online system to facilitate performing tasks of new types (2026-03-10),
15. 12548055 - Using a generative artificial intelligence model to generate a personalized image of a catalog item (2026-02-10),

Title: Naval Shah - Innovator in Price Sensitivity Prediction

Introduction

Naval Shah is a notable inventor based in Toronto, Canada. He has made significant contributions to the field of predictive modeling, particularly in understanding user price sensitivity. His innovative approach leverages data acquired from in-store sensors to enhance online shopping experiences.

Latest Patents

Naval Shah holds 1 patent for his invention titled "Using a trained model to predict a user's price sensitivity based on data acquired from in-store sensors." This patent describes a system that utilizes a trained model to determine a price sensitivity feature for users of an online platform. The system gathers input data through a user interface and in-store behavior data, applying a price sensitivity model to predict a score indicative of the user's price sensitivity. Based on this score, the system identifies actions to prompt users to convert items, thereby enhancing the shopping experience.

Career Highlights

Naval Shah is currently employed at Maplebear Inc., where he continues to innovate in the realm of data-driven solutions. His work focuses on integrating technology with consumer behavior to create more effective online retail strategies.

Collaborations

Some of his notable coworkers include Brent Scheibelhut and Charles Wesley, who contribute to the collaborative environment at Maplebear Inc. Their combined expertise fosters innovation and drives the development of cutting-edge solutions.

Conclusion

Naval Shah's work exemplifies the intersection of technology and consumer behavior, showcasing how data can be harnessed to improve user experiences in online shopping. His contributions to predictive modeling are paving the way for future innovations in the retail sector.

Profile summary based on public USPTO records.
Data Sources: USPTO Patent Grant XML, Patent Center, EPO & CIPO • Normalized by IDiyas Innovation Graph. Methodology & provenance architecturePlease report any incorrect information to [email protected]
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