San Jose, CA, United States of America

Pankti Jayesh Kansara


Average Co-Inventor Count = 5.0

ph-index = 1

Forward Citations = 2(Granted Patents)


Company Filing History:


Years Active: 2023-2024

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2 patents (USPTO):Explore Patents

Title: Pankti Jayesh Kansara: Innovator in Transaction Prediction Technologies

Introduction

Pankti Jayesh Kansara is a notable inventor based in San Jose, California. He has made significant contributions to the field of transaction prediction technologies, holding two patents that enhance the accuracy of forecasting transaction quantities and dates.

Latest Patents

Kansara's latest patents focus on proactively predicting transaction quantities and dates based on sparse transaction data. The first patent involves systems and methods for predicting demand by analyzing historical transaction data across various categories of transacted items. This method organizes categories using a hierarchical structure and iterates through multiple levels to identify features for a quantity forecasting model. The model is trained to generate predicted quantity information for future transaction dates.

The second patent similarly addresses the prediction of transaction dates. It includes a method for receiving requests to forecast transaction dates for multiple entities. Historical data is again utilized, and various transaction date prediction models are trained and tested. The most accurate model is selected to predict future transaction dates, ensuring a high level of precision in forecasting.

Career Highlights

Pankti Jayesh Kansara is currently employed at SAP SE, where he applies his expertise in transaction prediction technologies. His work contributes to the development of innovative solutions that enhance business operations and decision-making processes.

Collaborations

Kansara collaborates with talented professionals such as James Rapp and Mario Ponce Midence, who contribute to the advancement of their projects and innovations.

Conclusion

Pankti Jayesh Kansara is a distinguished inventor whose work in transaction prediction technologies has the potential to transform how businesses forecast demand and manage transactions. His contributions are invaluable in the realm of data-driven decision-making.

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