Patents by Inventor Ajil Jalal

Ajil Jalal 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).

  • Patent number: 12380177
    Abstract: Techniques regarding root cause analyses based on time series data are provided. For example, one or more embodiments described herein can comprise a system, which can comprise a memory that can store computer executable components. The system can also comprise a processor, operably coupled to the memory, and that can execute the computer executable components stored in the memory. The computer executable components can comprise maintenance component that can detect a cause of failure for a mechanical system by employing a greedy hill climbing process to perform a polynomial number of conditional independence tests to determine a Granger causality between variables from time series data of the mechanical system given a conditioning set.
    Type: Grant
    Filed: October 20, 2023
    Date of Patent: August 5, 2025
    Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
    Inventors: Ajil Jalal, Karthikeyan Shanmugam, Bhanukiran Vinzamuri
  • Publication number: 20240160694
    Abstract: Techniques regarding root cause analyses based on time series data are provided. For example, one or more embodiments described herein can comprise a system, which can comprise a memory that can store computer executable components. The system can also comprise a processor, operably coupled to the memory, and that can execute the computer executable components stored in the memory. The computer executable components can comprise maintenance component that can detect a cause of failure for a mechanical system by employing a greedy hill climbing process to perform a polynomial number of conditional independence tests to determine a Granger causality between variables from time series data of the mechanical system given a conditioning set.
    Type: Application
    Filed: October 20, 2023
    Publication date: May 16, 2024
    Inventors: Ajil Jalal, Karthikeyan Shanmugam, Bhanukiran Vinzamuri
  • Patent number: 11816178
    Abstract: Techniques regarding root cause analyses based on time series data are provided. For example, one or more embodiments described herein can comprise a system, which can comprise a memory that can store computer executable components. The system can also comprise a processor, operably coupled to the memory, and that can execute the computer executable components stored in the memory. The computer executable components can comprise maintenance component that can detect a cause of failure for a mechanical system by employing a greedy hill climbing process to perform a polynomial number of conditional independence tests to determine a Granger causality between variables from time series data of the mechanical system given a conditioning set.
    Type: Grant
    Filed: December 9, 2021
    Date of Patent: November 14, 2023
    Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
    Inventors: Ajil Jalal, Karthikeyan Shanmugam, Bhanukiran Vinzamuri
  • Publication number: 20220100817
    Abstract: Techniques regarding root cause analyses based on time series data are provided. For example, one or more embodiments described herein can comprise a system, which can comprise a memory that can store computer executable components. The system can also comprise a processor, operably coupled to the memory, and that can execute the computer executable components stored in the memory. The computer executable components can comprise maintenance component that can detect a cause of failure for a mechanical system by employing a greedy hill climbing process to perform a polynomial number of conditional independence tests to determine a Granger causality between variables from time series data of the mechanical system given a conditioning set.
    Type: Application
    Filed: December 9, 2021
    Publication date: March 31, 2022
    Inventors: Ajil Jalal, Karthikeyan Shanmugam, Bhanukiran Vinzamuri
  • Patent number: 11238129
    Abstract: Techniques regarding root cause analyses based on time series data are provided. For example, one or more embodiments described herein can comprise a system, which can comprise a memory that can store computer executable components. The system can also comprise a processor, operably coupled to the memory, and that can execute the computer executable components stored in the memory. The computer executable components can comprise maintenance component that can detect a cause of failure for a mechanical system by employing a greedy hill climbing process to perform a polynomial number of conditional independence tests to determine a Granger causality between variables from time series data of the mechanical system given a conditioning set.
    Type: Grant
    Filed: December 11, 2019
    Date of Patent: February 1, 2022
    Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
    Inventors: Ajil Jalal, Karthikeyan Shanmugam, Bhanukiran Vinzamuri
  • Publication number: 20210182358
    Abstract: Techniques regarding root cause analyses based on time series data are provided. For example, one or more embodiments described herein can comprise a system, which can comprise a memory that can store computer executable components. The system can also comprise a processor, operably coupled to the memory, and that can execute the computer executable components stored in the memory. The computer executable components can comprise maintenance component that can detect a cause of failure for a mechanical system by employing a greedy hill climbing process to perform a polynomial number of conditional independence tests to determine a Granger causality between variables from time series data of the mechanical system given a conditioning set.
    Type: Application
    Filed: December 11, 2019
    Publication date: June 17, 2021
    Inventors: Ajil Jalal, Karthikeyan Shanmugam, Bhanukiran Vinzamuri