Patents by Inventor Nicholas Castro

Nicholas Castro 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).

  • Publication number: 20230342680
    Abstract: A machine learning (ML) process can include teaching, with a teaching set, a first ML algorithm to generate one or more machine-predicted results. One or more weights can be generated based on the one or more machine-predicted results and the teaching set. A second ML algorithm can be generated based on the one or more weights. Via the second ML algorithm, one or more machine-learned results can be generated. A description of one or more candidates can be received. Based on the one or more machine-learned results, a respective likelihood of interest in a CCG class of positions for each of the one or more candidates can be generated. A respective communication can be transmitted to each of a subset of the one or more candidates open to the respective likelihood of interest in the CCG class of positions for the subset above a threshold.
    Type: Application
    Filed: June 26, 2023
    Publication date: October 26, 2023
    Inventors: Christina R. Petrosso, Joseph W. Hanna, Nicholas Castro, David Trachtenberg
  • Patent number: 11727328
    Abstract: A machine learning (ML) process can include teaching, with a teaching set, a first ML algorithm to generate one or more machine-predicted results. One or more weights can be generated based on the one or more machine-predicted results and the teaching set. A second ML algorithm can be generated based on the one or more weights. Via the second ML algorithm, one or more machine-learned results can be generated. A description of one or more candidates can be received. Based on the one or more machine-learned results, a respective likelihood of interest in a CCG class of positions for each of the one or more candidates can be generated. A respective communication can be transmitted to each of a subset of the one or more candidates open to the respective likelihood of interest in the CCG class of positions for the subset above a threshold.
    Type: Grant
    Filed: October 5, 2020
    Date of Patent: August 15, 2023
    Assignee: MAGNIT JMM, LLC
    Inventors: Christina R. Petrosso, Joseph W. Hanna, Nicholas Castro, David Trachtenberg
  • Publication number: 20210103876
    Abstract: A machine learning (ML) process can include teaching, with a teaching set, a first ML algorithm to generate one or more machine-predicted results. One or more weights can be generated based on the one or more machine-predicted results and the teaching set. A second ML algorithm can be generated based on the one or more weights. Via the second ML algorithm, one or more machine-learned results can be generated. A description of one or more candidates can be received. Based on the one or more machine-learned results, a respective likelihood of interest in a CCG class of positions for each of the one or more candidates can be generated. A respective communication can be transmitted to each of a subset of the one or more candidates open to the respective likelihood of interest in the CCG class of positions for the subset above a threshold.
    Type: Application
    Filed: October 5, 2020
    Publication date: April 8, 2021
    Inventors: Christina R. Petrosso, Joseph W. Hanna, Nicholas Castro, David Trachtenberg