Patents by Inventor Ruochen Zha

Ruochen Zha 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: 20240303553
    Abstract: This application describes systems and methods for generating machine learning models (MLMs). An exemplary method includes obtaining a sample and user input data characterizing a product or service. A subset of the data is selected from the sample based on sampling the sample according to the user input data. An MLM is trained by applying the data subset as training input to the MLM, thereby providing a trained MLM to emulate a customer selection process unique to the product or service. A user interface (UI) configured to receive other user input data and cause the trained MLM to execute on the other user input data, thereby testing the trained MLM, is presented. A summary of results from the execution of the trained MLM is generated and presented in the UI. The summary of results indicates a contribution to the trained MLM of each of a plurality of features.
    Type: Application
    Filed: April 29, 2024
    Publication date: September 12, 2024
    Inventors: David Sheehan, Siavash Yasani, Bingjia Wang, Yunyan Zhang, Qiumeng Yu, Ruochen Zha, Adam Kleinman, Sean Javad Kamkar, Lingzhi Du, Saar Yalov, Jerome Louis Budzik
  • Patent number: 11972338
    Abstract: This application describes systems and methods for generating machine learning models (MLMs). An exemplary method includes obtaining a sample and user input data characterizing a product or service. A subset of the data is selected from the sample based on sampling the sample according to the user input data. An MLM is trained by applying the data subset as training input to the MLM, thereby providing a trained MLM to emulate a customer selection process unique to the product or service. A user interface (UI) configured to receive other user input data and cause the trained MLM to execute on the other user input data, thereby testing the trained MLM, is presented. A summary of results from the execution of the trained MLM is generated and presented in the UI. The summary of results indicates a contribution to the trained MLM of each of a plurality of features.
    Type: Grant
    Filed: May 2, 2023
    Date of Patent: April 30, 2024
    Assignee: ZestFinance, Inc.
    Inventors: David Sheehan, Siavash Yasini, Bingjia Wang, Yunyan Zhang, Qiumeng Yu, Ruochen Zha, Adam Kleinman, Sean Javad Kamkar, Lingzhi Du, Saar Yalov, Jerome Louis Budzik
  • Publication number: 20230359944
    Abstract: This application describes systems and methods for generating machine learning models (MLMs). An exemplary method includes obtaining a sample and user input data characterizing a product or service. A subset of the data is selected from the sample based on sampling the sample according to the user input data. An MLM is trained by applying the data subset as training input to the MLM, thereby providing a trained MLM to emulate a customer selection process unique to the product or service. A user interface (UI) configured to receive other user input data and cause the trained MLM to execute on the other user input data, thereby testing the trained MLM, is presented. A summary of results from the execution of the trained MLM is generated and presented in the UI. The summary of results indicates a contribution to the trained MLM of each of a plurality of features.
    Type: Application
    Filed: May 2, 2023
    Publication date: November 9, 2023
    Inventors: David Sheehan, Siavash Yasini, Bingjia Wang, Yunyan Zhang, Qiumeng Yu, Ruochen Zha, Adam Kleinman, Sean Javad Kamkar, Lingzhi Du, Saar Yalov, Jerome Louis Budzik