Keegan Nesbitt

Title: Keegan Nesbitt’s Patents in Machine Learning and Data Processing.

Introduction

Keegan Nesbitt is an inventor based in Louisville, Kentucky, whose patent work focuses on systems for developing and deploying machine-learning models. He is associated with Humana Inc. and holds 2 patents.

Latest Patents

Nesbitt’s two listed patents address related approaches to making machine-learning development more efficient.

“Machine Learning Platform and Feature Generation for Efficient Data Processing” describes a system that standardizes model training and deployment to reduce redundant work. It prepares and de-sensitizes data, then stores reusable features so different models and training modules can access them without repeatedly adjusting the data. The system also supports defining evaluation cohorts, selecting model templates and features, conducting experiments, and recording training artifacts and model settings for later execution.

“Machine Learning Platform and Pipeline for Efficient Data Processing” describes a similar workflow for coordinating model development. It covers preparing reusable features, establishing evaluation cohorts, selecting templates and features, evaluating models, and storing training artifacts and execution settings in shared systems.

Career Highlights

The patents reflect an emphasis on reusable data infrastructure and standardized machine-learning workflows. By organizing features, model artifacts, and deployment settings for shared access, the described systems aim to help data scientists develop and operationalize models with less duplicated effort.

Collaborations

Nesbitt is associated with Humana Inc. His listed coworkers include David Christopher Mack and Rajagopal Subramanian.

Conclusion

Keegan Nesbitt’s patent portfolio centers on machine-learning platforms and pipelines designed to streamline data preparation, model experimentation, and deployment.