Patents by Inventor Fayaz Shaik

Fayaz Shaik 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).

  • Wage garnishments processing using machine learning for predicting field values
    Patent number: 11551318
    Abstract: An illustrative embodiment provides a computer-implemented method for processing wage garnishment court orders includes obtaining a court order for wage garnishment for a user. The method also includes predicting values for a first subset of a number of fields for executing wage garnishment according to the court order using a rule engine. The method also includes predicting values for a second subset of the number of fields using a machine learning engine, wherein the second subset of the number of fields includes missing fields for which the rule engine could not provide a prediction. The machine learning engine includes one of a plurality of classification algorithms. The one of the plurality of classification algorithms selected to use for the machine learning engine for predicting field values is selected according to at least one of accuracy, speed, size of model, and explainability.
    Type: Grant
    Filed: July 22, 2019
    Date of Patent: January 10, 2023
    Assignee: ADP, Inc.
    Inventors: Azhar Khan, Arjun Hegde, Dhirendra Kumar, Fayaz Shaik, Srinivas Kulkarni, Ravi Kumar Tadysetty
  • WAGE GARNISHMENTS PROCESSING USING MACHINE LEARNING FOR PREDICTING FIELD VALUES
    Publication number: 20210027403
    Abstract: An illustrative embodiment provides a computer-implemented method for processing wage garnishment court orders includes obtaining a court order for wage garnishment for a user. The method also includes predicting values for a first subset of a number of fields for executing wage garnishment according to the court order using a rule engine. The method also includes predicting values for a second subset of the number of fields using a machine learning engine, wherein the second subset of the number of fields includes missing fields for which the rule engine could not provide a prediction. The machine learning engine includes one of a plurality of classification algorithms. The one of the plurality of classification algorithms selected to use for the machine learning engine for predicting field values is selected according to at least one of accuracy, speed, size of model, and explainability.
    Type: Application
    Filed: July 22, 2019
    Publication date: January 28, 2021
    Inventors: Azhar Khan, Arjun Hegde, Dhirendra Kumar, Fayaz Shaik, Srinivas Kulkarni, Ravi Kumar Tadysetty