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Years Active: 2014
Title: Innovations by Peter Hofmann in Machine Learning for Power Grids
Introduction
Peter Hofmann is an accomplished inventor based in Hasbrouck Heights, NJ (US). He has made significant contributions to the field of machine learning, particularly in applications related to power grids. His innovative approach focuses on enhancing the reliability and efficiency of electrical systems through advanced data processing techniques.
Latest Patents
Peter Hofmann holds a patent for a machine learning system designed for ranking a collection of filtered propensity to failure metrics of similar components within an electrical grid. This patent outlines a comprehensive system that includes a raw data assembly to provide representative data of like components, a data processor to convert raw data into more uniform data, and a database to store this processed information. Additionally, it features a machine learning engine that generates propensity to failure metrics, an evaluation engine to filter non-compliant metrics, and a decision support application that displays a ranking of these metrics.
Career Highlights
Throughout his career, Peter Hofmann has worked with prestigious organizations such as Columbia University and Consolidated Edison Company of New York, Inc. His experience in these institutions has allowed him to collaborate with leading experts in the field and contribute to groundbreaking research and development projects.
Collaborations
Peter has had the opportunity to work alongside notable colleagues, including Roger N. Anderson and Albert Boulanger. Their combined expertise has fostered an environment of innovation and creativity, leading to advancements in machine learning applications for power systems.
Conclusion
Peter Hofmann's work in machine learning for power grids exemplifies the intersection of technology and electrical engineering. His contributions are paving the way for more reliable and efficient power systems, showcasing the importance of innovation in today's energy landscape.