Porto Alegre, Brazil

Leonardo Santos

This inventor holds 3 USPTO granted patents and 4 published patent applications. Top assignee: Adp, Inc.. Active years: 2022-2026.

USPTO Granted Patents = 3 

% Patents Active = 100.0

Average Co-Inventor Count = 6.2

ph-index = 1


Company Filing History:


Years Active: 2022-2026

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3 patents (USPTO):Explore Patents

Title: Innovations by Leonardo Santos

Introduction

Leonardo Santos is an accomplished inventor based in Porto Alegre, Brazil. He has made significant contributions to the field of technology, particularly in the area of credit eligibility prediction. With a total of 3 patents to his name, Santos continues to push the boundaries of innovation.

Latest Patents

One of his notable patents is a Credit Eligibility Predictor. This invention involves extracting aspects from payroll data of employees within an organization. It utilizes historical data associated with previous instances of certified tax credit eligibility. The process normalizes the extracted data concerning data type and value. A neural network classifier generates multi-class outputs for each employee, indicating the likelihood of eligibility for various tax credits. The system filters the normalized data by removing portions linked to employees deemed ineligible, creating a remainder set of data for those who are eligible. Finally, it prioritizes applications for tax credits based on respective values and likelihoods of eligibility.

Career Highlights

Leonardo Santos works at ADP, Inc., where he applies his expertise in developing innovative solutions. His work has had a significant impact on how organizations manage tax credit eligibility, streamlining processes and improving efficiency.

Collaborations

Some of his coworkers include Stefan Zanona and Anjo Costa, who contribute to the collaborative environment at ADP, Inc. Their teamwork fosters innovation and enhances the development of new technologies.

Conclusion

Leonardo Santos exemplifies the spirit of innovation through his work and patents. His contributions to credit eligibility prediction demonstrate the potential of technology to improve organizational processes.

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