Patents by Inventor Ritwik Mitra

Ritwik Mitra 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: 20240296519
    Abstract: Systems and methods for media generation are provided. According to one aspect, a method for media generation includes obtaining a media object and context data describing a context of the media object, wherein the media object comprises one or more modification parameters; generating a modified media object by adjusting the one or more modification parameters using a reinforcement learning model based on the context data; and providing the modified media object within the context.
    Type: Application
    Filed: March 3, 2023
    Publication date: September 5, 2024
    Inventors: Pooja Guhan, Saayan Mitra, Somdeb Sarkhel, Ritwik Sinha, Stefano Petrangeli, Viswanathan Swaminathan
  • Publication number: 20240256926
    Abstract: Aspects of the subject disclosure may include, for example, system and apparatus that enable operations that may include receiving, by a processing system, project data defining a proposed machine learning (ML) project of an entity and storing the project data in a project database with other project data for other projects. The operations may further include extracting extracted features of the proposed project and, based on the extracted features, determining a clustering assignment for the proposed project. Determining the clustering assignment may comprise comparing information about the proposed project including the extracted features with information about the other projects and assigning the proposed project to a cluster including one or more projects having similar bias characteristics as the proposed project. The operations may further include determining a risk of potential bias for the proposed project and, based on the risk of bias, recommending a corrective action to reduce the risk of bias.
    Type: Application
    Filed: April 11, 2024
    Publication date: August 1, 2024
    Applicant: AT&T Intellectual Property I, L.P.
    Inventors: Emily Dodwell, Balachander Krishnamurthy, Rajat Malik, Ritwik Mitra
  • Patent number: 11983646
    Abstract: Aspects of the subject disclosure may include, for example, system and apparatus that enable operations that may include receiving, by a processing system, project data defining a proposed machine learning (ML) project of an entity and storing the project data in a project database with other project data for other projects. The operations may further include extracting extracted features of the proposed project and, based on the extracted features, determining a clustering assignment for the proposed project. Determining the clustering assignment may comprise comparing information about the proposed project including the extracted features with information about the other projects and assigning the proposed project to a cluster including one or more projects having similar bias characteristics as the proposed project. The operations may further include determining a risk of potential bias for the proposed project and, based on the risk of bias, recommending a corrective action to reduce the risk of bias.
    Type: Grant
    Filed: February 22, 2023
    Date of Patent: May 14, 2024
    Assignee: AT&T Intellectual Property I, L.P.
    Inventors: Emily Dodwell, Balachander Krishnamurthy, Rajat Malik, Ritwik Mitra
  • Publication number: 20230259796
    Abstract: Aspects of the subject disclosure may include, for example, system and apparatus that enable operations that may include receiving, by a processing system, project data defining a proposed machine learning(ML) project of an entity and storing the project data in a project database with other project data for other projects. The operations may further include extracting extracted features of the proposed project and, based on the extracted features, determining a clustering assignment for the proposed project. Determining the clustering assignment may comprise comparing information about the proposed project including the extracted features with information about the other projects and assigning the proposed project to a cluster including one or more projects having similar bias characteristics as the proposed project. The operations may further include determining a risk of potential bias for the proposed project and, based on the risk of bias, recommending a corrective action to reduce the risk of bias.
    Type: Application
    Filed: February 22, 2023
    Publication date: August 17, 2023
    Applicant: AT&T Intellectual Property I, L.P.
    Inventors: Emily Dodwell, Balachander Krishnamurthy, Rajat Malik, Ritwik Mitra
  • Patent number: 11620542
    Abstract: Aspects of the subject disclosure may include, for example, system and apparatus that enable operations that may include receiving, by a processing system, project data defining a proposed machine learning (ML) project of an entity and storing the project data in a project database with other project data for other projects. The operations may further include extracting extracted features of the proposed project and, based on the extracted features, determining a clustering assignment for the proposed project. Determining the clustering assignment may comprise comparing information about the proposed project including the extracted features with information about the other projects and assigning the proposed project to a cluster including one or more projects having similar bias characteristics as the proposed project. The operations may further include determining a risk of potential bias for the proposed project and, based on the risk of bias, recommending a corrective action to reduce the risk of bias.
    Type: Grant
    Filed: December 5, 2019
    Date of Patent: April 4, 2023
    Assignee: AT&T Intellectual Property I, L.P.
    Inventors: Emily Dodwell, Balachander Krishnamurthy, Rajat Malik, Ritwik Mitra
  • Patent number: 11586950
    Abstract: Aspects of the disclosure include, for example, obtaining input data. Further embodiments include a determination of a fast path prediction for a first time period according to the input data based on a fast path model. Embodiments include providing instructions to deliver information to a user device according to the fast path prediction. Additional embodiments include obtaining additional input data. Embodiments include a determination of a slow path prediction for the first time period according to the input data and the additional input data based on a slow path model, retraining the fast path model according to the input data and the fast path prediction, and training the slow path model according to the slow path prediction. Embodiments include a determination of a fast path negative impact metric and determination of a slow path negative impact metric. Other embodiments are disclosed.
    Type: Grant
    Filed: December 6, 2019
    Date of Patent: February 21, 2023
    Assignee: AT&T Intellectual Property I, L.P.
    Inventors: Emily Dodwell, Balachander Krishnamurthy, Ritwik Mitra
  • Publication number: 20220005077
    Abstract: Aspects of the subject disclosure may include, for example, embodiments receiving a notification of actions, determining a potential bias metric for the actions in response to analyzing the actions using a machine learning application, determining the potential bias metric for the actions is above a potential bias threshold for the actions, and adjusting the actions to mitigate potential bias in the actions according to the potential bias metric being above the potential bias threshold using the machine learning application. Further embodiments can include determining a potential bias metric for the adjusted actions in response to analyzing the adjusted actions using the machine learning application, determining the potential bias metric for the adjusted actions is below the potential bias threshold for the actions, and providing a notification that indicates to implement the adjusted actions. Other embodiments are disclosed.
    Type: Application
    Filed: July 2, 2020
    Publication date: January 6, 2022
    Applicant: AT&T Intellectual Property I, L.P.
    Inventors: Balachander Krishnamurthy, Subhabrata Majumdar, Ritwik Mitra, David Poole
  • Publication number: 20210174222
    Abstract: Aspects of the subject disclosure may include, for example, system and apparatus that enable operations that may include receiving, by a processing system, project data defining a proposed machine learning (ML) project of an entity and storing the project data in a project database with other project data for other projects. The operations may further include extracting extracted features of the proposed project and, based on the extracted features, determining a clustering assignment for the proposed project. Determining the clustering assignment may comprise comparing information about the proposed project including the extracted features with information about the other projects and assigning the proposed project to a cluster including one or more projects having similar bias characteristics as the proposed project. The operations may further include determining a risk of potential bias for the proposed project and, based on the risk of bias, recommending a corrective action to reduce the risk of bias.
    Type: Application
    Filed: December 5, 2019
    Publication date: June 10, 2021
    Applicant: AT&T Intellectual Property I, L.P.
    Inventors: Emily Dodwell, Balachander Krishnamurthy, Rajat Malik, Ritwik Mitra
  • Publication number: 20210174223
    Abstract: Aspects of the disclosure include, for example, obtaining input data. Further embodiments include a determination of a fast path prediction for a first time period according to the input data based on a fast path model. Embodiments include providing instructions to deliver information to a user device according to the fast path prediction. Additional embodiments include obtaining additional input data. Embodiments include a determination of a slow path prediction for the first time period according to the input data and the additional input data based on a slow path model, retraining the fast path model according to the input data and the fast path prediction, and training the slow path model according to the slow path prediction. Embodiments include a determination of a fast path negative impact metric and determination of a slow path negative impact metric. Other embodiments are disclosed.
    Type: Application
    Filed: December 6, 2019
    Publication date: June 10, 2021
    Applicant: AT&T Intellectual Property I, L.P.
    Inventors: Emily Dodwell, Balachander Krishnamurthy, Ritwik Mitra