Austin, TX, United States of America

Andrew J Laforteza


Average Co-Inventor Count = 4.4

ph-index = 1

Forward Citations = 5(Granted Patents)


Company Filing History:


Years Active: 2019-2021

where 'Filed Patents' based on already Granted Patents

4 patents (USPTO):

Title: The Innovations of Andrew J Laforteza

Introduction

Andrew J Laforteza is an accomplished inventor based in Austin, TX. He has made significant contributions to the field of machine learning, particularly in the area of storage volume reclamation. With a total of four patents to his name, Laforteza's work has garnered attention for its innovative approach to storage maintenance.

Latest Patents

Laforteza's latest patents focus on machine learning techniques for determining the confidence in reclaiming storage volumes. One of his notable inventions describes a method, system, and computer product for performing storage maintenance. This invention involves receiving a training set for storage volume reclamation, which contains sets of storage parameters and corresponding user decisions regarding the reclaimability of storage volumes. The training set is utilized to train a machine learning system to identify reclaimable candidate storage volumes. The trained system can then assess whether a candidate storage volume is likely reclaimable based on its parameters.

Career Highlights

Laforteza is currently employed at International Business Machines Corporation (IBM), where he continues to innovate in the field of technology. His work has not only advanced the understanding of storage systems but has also provided practical solutions for improving storage maintenance processes.

Collaborations

Throughout his career, Laforteza has collaborated with notable colleagues, including John A Bowers and Ryan D McNair. These collaborations have contributed to the development of his innovative patents and have fostered a productive environment for technological advancement.

Conclusion

Andrew J Laforteza is a prominent inventor whose work in machine learning and storage volume reclamation has made a significant impact in the technology sector. His contributions continue to shape the future of storage maintenance and machine learning applications.

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