Patents by Inventor Nicolas Leazard

Nicolas Leazard has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Framework for failure detection, forecasting and remediation combining domain-specific telemetry and customized machine learning models
    Patent number: 12596599
    Abstract: Techniques for providing a centralized framework for forecasting IT component failures. The techniques include collecting raw telemetry data specific to different IT component domains, and transforming the telemetry data into structured telemetry data. The techniques include performing feature engineering on the structured telemetry data to obtain features relevant to IT component failures in each IT component domain, and, for each IT component domain, using the features to generate a customized ML model. The techniques include accessing features relevant to IT component failures in each IT component domain, accessing a customized ML model for forecasting IT component failures in the IT component domain, and forecasting IT component failures in the IT component domain using the customized ML model.
    Type: Grant
    Filed: August 5, 2024
    Date of Patent: April 7, 2026
    Assignee: Dell Products L.P.
    Inventors: Arun Rameshbabu, Shaul Dar, David Sydow, Shreyans Jasoriya, Keith Drummond, Nicolas Leazard
  • FRAMEWORK FOR FAILURE DETECTION, FORECASTING AND REMEDIATION COMBINING DOMAIN-SPECIFIC TELEMETRY AND CUSTOMIZED MACHINE LEARNING MODELS
    Publication number: 20260037352
    Abstract: Techniques for providing a centralized framework for forecasting IT component failures. The techniques include collecting raw telemetry data specific to different IT component domains, and transforming the telemetry data into structured telemetry data. The techniques include performing feature engineering on the structured telemetry data to obtain features relevant to IT component failures in each IT component domain, and, for each IT component domain, using the features to generate a customized ML model. The techniques include accessing features relevant to IT component failures in each IT component domain, accessing a customized ML model for forecasting IT component failures in the IT component domain, and forecasting IT component failures in the IT component domain using the customized ML model.
    Type: Application
    Filed: August 5, 2024
    Publication date: February 5, 2026
    Inventors: Arun Rameshbabu, Shaul Dar, David Sydow, Shreyans Jasoriya, Keith Drummond, Nicolas Leazard