Patents by Inventor Liam R. Cusack

Liam R. Cusack 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).

  • Method and apparatus for providing efficient testing of systems by using artificial intelligence tools
    Patent number: 11403554
    Abstract: An artificial intelligence testing apparatus may include processing circuitry configured to execute instructions that, when executed, cause the apparatus to create initial sample points based on a simulation received at the apparatus, and employ cyclic evaluation of the simulation until a stopping criteria is met. Employing the cyclic evaluation includes running the simulation at design points for a set of queries associated with a current iteration of the cyclic evaluation, training a set of meta-models of parameter space associated with the simulation for the current iteration, computing a set of metrics for the current iteration, and employing a selected sampling approach to select a new set of design points for a next iteration of the cyclic evaluation.
    Type: Grant
    Filed: January 29, 2019
    Date of Patent: August 2, 2022
    Assignee: The Johns Hopkins University
    Inventors: Matthew B. Wagner, David R. Witman, Peter A. Sevich, Patrick J. Trainor, Liam R. Cusack, William A. Patterson
  • METHOD AND APPARATUS FOR PROVIDING EFFICIENT TESTING OF SYSTEMS BY USING ARTIFICIAL INTELLIGENCE TOOLS
    Publication number: 20190236479
    Abstract: An artificial intelligence testing apparatus may include processing circuitry configured to execute instructions that, when executed, cause the apparatus to create initial sample points based on a simulation received at the apparatus, and employ cyclic evaluation of the simulation until a stopping criteria is met. Employing the cyclic evaluation includes running the simulation at design points for a set of queries associated with a current iteration of the cyclic evaluation, training a set of meta-models of parameter space associated with the simulation for the current iteration, computing a set of metrics for the current iteration, and employing a selected sampling approach to select a new set of design points for a next iteration of the cyclic evaluation.
    Type: Application
    Filed: January 29, 2019
    Publication date: August 1, 2019
    Inventors: Matthew B. Wagner, David R. Witman, Peter A. Sevich, Patrick J. Trainor, Liam R. Cusack, William A. Patterson