Matthew Seal

Title: Matthew Seal - Innovator in Predictive Modeling and Hierarchical Visualization

Introduction

Matthew Seal is an accomplished inventor based in Sunnyvale, CA. He has made significant contributions to the fields of predictive modeling and hierarchical data visualization. With a total of 2 patents, his work focuses on enhancing the efficiency and accuracy of data analysis.

Latest Patents

Matthew's latest patents include "Auto-selection of hierarchically-related near-term forecasting models" and "Hierarchical information visualizer and editor." The first patent discloses techniques for selecting a predictive model to analyze hierarchical data. It involves receiving first time series data representing current activity and retrieving second time series data from a prior period. Predictive models are then generated using this data, with scores assigned based on statistical outcomes compared to the first time series data. The models are ranked according to these scores. The second patent outlines methods for generating visualizations of organized hierarchy structures. An editor tool allows users to interact with a graphical representation of a tree structure, enabling the identification and visualization of hierarchy paths associated with selected elements.

Career Highlights

Matthew Seal is currently employed at OpenGov, Inc., where he applies his expertise in predictive modeling and data visualization. His innovative approaches have contributed to the development of advanced tools that enhance data analysis capabilities.

Collaborations

Some of Matthew's notable coworkers include Gabor Melli and Morgan Keys, who collaborate with him on various projects at OpenGov, Inc.

Conclusion

Matthew Seal is a prominent inventor whose work in predictive modeling and hierarchical visualization continues to impact the field of data analysis. His patents reflect a commitment to innovation and efficiency in handling complex data structures.