Auburn, ME, United States of America

Daniel Alfonsetti

USPTO Granted Patents = 3 

Average Co-Inventor Count = 2.0

ph-index = 1


Company Filing History:


Years Active: 2023-2025

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3 patents (USPTO):Explore Patents

Title: Innovations of Daniel Alfonsetti

Introduction

Daniel Alfonsetti is an accomplished inventor based in Auburn, ME (US). He has made significant contributions to the field of data management in vehicle operations, holding a total of 3 patents. His work focuses on enhancing the efficiency and effectiveness of data storage and machine learning in autonomous vehicles.

Latest Patents

One of Alfonsetti's latest patents is titled "Methods and systems for managing data storage in vehicle operations." This patent discloses various embodiments for managing data generated by onboard systems of a vehicle. The system involves a processor that receives messages from these systems and saves them according to specific data logging policies. Another notable patent is "Systems and methods for intelligent selection of data for building a machine learning model." This invention outlines methods for selecting data to train machine learning models using active learning, focusing on identifying trends in sensor data logs from autonomous vehicles.

Career Highlights

Throughout his career, Alfonsetti has worked with prominent companies in the automotive and technology sectors. He has been associated with Volkswagen Group of America Investments, LLC and Argo AI GmbH, where he has contributed to innovative projects that push the boundaries of vehicle technology.

Collaborations

Alfonsetti has collaborated with talented professionals in his field, including Jelena Frtunikj and John Russell Lepird. These collaborations have fostered an environment of innovation and creativity, leading to advancements in vehicle data management.

Conclusion

Daniel Alfonsetti's work exemplifies the spirit of innovation in the automotive industry. His patents and career achievements reflect his commitment to improving data management and machine learning in vehicle operations.

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