Patents by Inventor Nishitha Kakani

Nishitha Kakani 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).

  • Personal Data Discovery
    Publication number: 20240346240
    Abstract: Artificial-intelligence computer-implemented processes and machines predict whether personal data may be present in structured software based on metadata field(s) contained therein. Natural language processing preprocesses input strings corresponding to the metadata field(s) into normalized input sequence(s). Individual characters in the sequence(s) are embedded into fixed-dimension vectors of real numbers. Bidirectional LSTM(s) or other machine-learning algorithm(s) are utilized to generate forward and backward contextualization(s). Neural network output(s) are provided based on element-wise averaging or feed forwarding based on the contextualization(s) in order to predict whether one or more value fields corresponding to the metadata field(s) may contain personal data.
    Type: Application
    Filed: June 24, 2024
    Publication date: October 17, 2024
    Inventors: Moncef El Ouriaghli, Nishitha Kakani, Sriram Mohanraj, Yanghong Shao, Timothy L. Atwell
  • Personal data discovery
    Patent number: 12050858
    Abstract: Artificial-intelligence computer-implemented processes and machines predict whether personal data may be present in structured software based on metadata field(s) contained therein. Natural language processing preprocesses input strings corresponding to the metadata field(s) into normalized input sequence(s). Individual characters in the sequence(s) are embedded into fixed-dimension vectors of real numbers. Bidirectional LSTM(s) or other machine-learning algorithm(s) are utilized to generate forward and backward contextualization(s). Neural network output(s) are provided based on element-wise averaging or feed forwarding based on the contextualization(s) in order to predict whether one or more value fields corresponding to the metadata field(s) may contain personal data.
    Type: Grant
    Filed: September 21, 2021
    Date of Patent: July 30, 2024
    Assignee: Bank of America Corporation
    Inventors: Moncef El Ouriaghli, Nishitha Kakani, Sriram Mohanraj, Yanghong Shao, Timothy L Atwell
  • Personal Data Discovery
    Publication number: 20230091581
    Abstract: Artificial-intelligence computer-implemented processes and machines predict whether personal data may be present in structured software based on metadata field(s) contained therein. Natural language processing preprocesses input strings corresponding to the metadata field(s) into normalized input sequence(s). Individual characters in the sequence(s) are embedded into fixed-dimension vectors of real numbers. Bidirectional LSTM(s) or other machine-learning algorithm(s) are utilized to generate forward and backward contextualization(s). Neural network output(s) are provided based on element-wise averaging or feed forwarding based on the contextualization(s) in order to predict whether one or more value fields corresponding to the metadata field(s) may contain personal data.
    Type: Application
    Filed: September 21, 2021
    Publication date: March 23, 2023
    Inventors: Moncef El Ouriaghli, Nishitha Kakani, Sriram Mohanraj, Yanghong Shao, Timothy L. Atwell