Samuel Bean

Title: Innovations of Samuel Bean in Machine Learning for Object Authentication

Introduction

Samuel Bean is an innovative inventor based in Ferndale, MI (US). He has made significant contributions to the field of machine learning, particularly in the area of object authentication. His work focuses on developing systems and methods that enhance the security of online activities.

Latest Patents

Samuel Bean holds a patent for "Machine learning techniques for object authentication." This patent describes systems and methods for authenticating objects associated with online activities. The authentication system accesses data related to a target object and generates a featurized dataframe by processing this data. A machine learning model is then applied to the featurized dataframe to determine an authenticity indicator for the target object. Based on this indicator, the target object is assigned to an authentication stream, which can either block or permit online activities involving the object.

Career Highlights

Samuel Bean is currently employed at StockX LLC, where he continues to apply his expertise in machine learning and object authentication. His innovative approach has the potential to significantly improve online security measures.

Collaborations

Some of his notable coworkers include Dominic Vena Roberts, II and Blaine Dietrich. Their collaboration contributes to the advancement of technology in their field.

Conclusion

Samuel Bean's work in machine learning and object authentication represents a significant advancement in online security. His innovative patent and contributions to StockX LLC highlight his role as a leading inventor in this important area.