Steven Dickerson

Title: The Innovative Mind of Steven Dickerson

Introduction

Steven Dickerson is a notable inventor based in Deerfield, IL (US), recognized for his contributions to the field of data science and machine learning. With a total of 4 patents to his name, he has developed innovative solutions that address bias in data models and enhance interpretability in machine learning.

Latest Patents

One of his latest patents is titled "Computing system and method for creating a data science model having reduced bias." This invention outlines a computing platform designed to train an initial model object using a machine learning process. The system identifies bias in the model and produces an updated version by replacing certain input variables with transformations, ultimately mitigating bias in the data science model.

Another significant patent is "System and method for utilizing grouped partial dependence plots and game-theoretic concepts and their extensions in the generation of adverse action reason codes." This framework interprets machine learning models by grouping input variables based on their dependencies. It employs clustering algorithms to define these groups and calculates scores related to each group, enhancing the understanding of model outputs.

Career Highlights

Throughout his career, Steven has worked with prominent companies such as Discover Financial Services LLC and Capital One Financial Corporation. His experience in these organizations has allowed him to apply his innovative ideas in practical settings, contributing to advancements in financial technology.

Collaborations

Steven has collaborated with talented individuals in his field, including Alexey Miroshnikov and Konstandinos Kotsiopoulos. These partnerships have fostered a creative environment that encourages the development of groundbreaking technologies.

Conclusion

Steven Dickerson's work exemplifies the spirit of innovation in the realm of data science and machine learning. His patents not only address critical issues such as bias but also enhance the interpretability of complex models. His contributions continue to shape the future of technology in meaningful ways.