Patents by Inventor Srinivas Chebolu

Srinivas Chebolu 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).

  • Automated feedback-based application optimization
    Patent number: 11086754
    Abstract: Approaches presented herein enable optimization of a developing application to a user base. More specifically, application-centric data is gathered during a cultivation phase of the developing application. Substantially concurrently with the cultivation phase of the developing application, the application-centric data is analyzed according to static code of the developing application, a testing of the developing application, or a user experience (UX) design of the developing application. A machine learning model is applied to the analyzed application-centric data. This machine learning model is trained on historic application feedback data from applications available to the user base. Based on the machine learning model, a recommended change to optimize the developing application to the user base is generated.
    Type: Grant
    Filed: July 2, 2019
    Date of Patent: August 10, 2021
    Assignee: International Business Machines Corporation
    Inventors: Manish Anand Bhide, Vijay Kumar Ananthapur Bache, Srinivas Chebolu, Jhilam Bera
  • AUTOMATED FEEDBACK-BASED APPLICATION OPTIMIZATION
    Publication number: 20210004311
    Abstract: Approaches presented herein enable optimization of a developing application to a user base. More specifically, application-centric data is gathered during a cultivation phase of the developing application. Substantially concurrently with the cultivation phase of the developing application, the application-centric data is analyzed according to static code of the developing application, a testing of the developing application, or a user experience (UX) design of the developing application. A machine learning model is applied to the analyzed application-centric data. This machine learning model is trained on historic application feedback data from applications available to the user base. Based on the machine learning model, a recommended change to optimize the developing application to the user base is generated.
    Type: Application
    Filed: July 2, 2019
    Publication date: January 7, 2021
    Inventors: Manish Anand Bhide, Vijay Kumar Ananthapur Bache, Srinivas Chebolu, Jhilam Bera