This inventor holds 1 USPTO granted patent and 1 published patent application. Top assignee: Intuit, Inc.. Active years: 2026.
Company Filing History:
Years Active: 2026
Title: Nathan Osborne - Innovator in Time-Series Data Featurization
Introduction
Nathan Osborne is a prominent inventor based in San Diego, CA. He has made significant contributions to the field of machine learning, particularly in the area of time-series data featurization. His innovative approach enhances the training of machine learning models, making them more effective in various applications.
Latest Patents
Nathan holds a patent for his work titled "Time-series data featurization." This patent outlines methods, systems, and apparatuses designed to featurize time-series data to improve machine learning model training. The process involves preprocessing transaction records to identify descriptive and categorical fields. A first machine learning model is used to assign categories, while tags are applied based on domain-specific patterns or large language models. The data is then organized into a star schema data structure, which includes a fact structure and associated dimension structures. Features are generated from this data structure based on time windows, incorporating statistical metrics and identified patterns. These features are subsequently provided to a machine learning module to train a second machine learning model, enhancing accuracy and adaptability for applications such as customer behavior prediction and financial analysis. This approach effectively addresses challenges related to high dimensionality, noise, and temporal dependencies in time-series data.
Career Highlights
Nathan is currently employed at Intuit, Inc., where he continues to develop innovative solutions in the field of data science and machine learning. His work has been instrumental in advancing the capabilities of machine learning applications, particularly in financial technology.
Collaborations
Nathan collaborates with talented individuals such as Kun Lu and Wei Wang, contributing to a dynamic and innovative work environment.
Conclusion
Nathan Osborne is a key figure in the realm of machine learning, with a focus on time-series data featurization. His contributions are paving the way for more accurate and adaptable machine learning models, which are essential for various applications in today's data-driven world.