Columbia University

Consolidated Edison Company of New York, Inc.

Phil Gross

Leon L Wu

Roger N Anderson

Albert Boulanger

Arthur Kressner

Maggie Chow

David Waltz

Haimonti Dutta

Huang Bert

Steve Ierome

Cynthia Rudin

Delfina Isaac

Rebecca J Passonneau

Axinia Radeva

Peter Hofmann

Ansaf Salleb-Aouissi

Frank Dougherty

A machine learning system for ranking a collection of filtered propensity to failure metrics of like components within an electrical grid that includes a raw data assembly to provide raw data representative of the like components within the electrical grid; (b) a data processor, operatively coupled to the raw data assembly, to convert the raw data to more uniform data via one or more data processing techniques; (c) a database, operatively coupled to the data processor, to store the more uniform data; (d) a machine learning engine, operatively coupled to the database, to provide a collection of propensity to failure metrics for the like components; (e) an evaluation engine, operatively coupled to the machine learning engine, to detect and remove non-complying metrics from the collection of propensity to failure metrics and to provide the collection of filtered propensity to failure metrics; and (f) a decision support application, operatively coupled to the evaluation engine, configured to display a ranking of the collection of filtered propensity to failure metrics of like components within the electrical grid.

Machine learning for power grid

Growing community of inventors

Brooklyn, NY, United States of America

Phil Gross