Patents by Inventor Lea VEGA ROMERO

Lea VEGA ROMERO 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: 20240152933
    Abstract: Techniques are described herein that are capable of automatic mapping of a question or compliance controls associated with a compliance standard to compliance controls associated with another compliance standard. Reference controls having respective first subsets of text-based features are identified. A question having a second subset of the text-based features or custom controls having respective second subsets of the text-based features are identified. Scores for the respective reference controls are determined for the question or each custom control using a supervised natural language processing machine learning model based at least on the first subsets of the text-based features and the second subset(s) of the text-based features. A compliance map is generated by automatically mapping the question or each custom control to a respective subset of the reference controls using the supervised natural language processing machine learning model based at least on the scores.
    Type: Application
    Filed: November 7, 2022
    Publication date: May 9, 2024
    Inventors: Jong-Chin LIN, Tianjing XU, Shashi KOSALRAM, Ryan Wang GAO, Shanshan LIU, Lea VEGA ROMERO, Xinjian XUE, Qi LIU, Sunitha Mary SAMUEL, Alan Si-Rui LUK
  • Patent number: 11775277
    Abstract: Technologies related to predicting whether a requested change (deployment) in a cloud computing environment will fail are described herein. An exposomic feature value is computed based upon a time series of risk values, where the risk values represent risk of failure over several historic time intervals. A probabilistic model computes a likelihood that the requested deployment will fail during implementation of the requested deployment based upon the exposomic feature value and a contextual feature value, and a notification is transmitted to a computing device of a change manager to allow the change manager to take remedial action.
    Type: Grant
    Filed: June 21, 2021
    Date of Patent: October 3, 2023
    Assignee: MICROSOFT TECHNOLOGY LICENSING, LLC
    Inventors: Xinjian Xue, Bin Pan, Naveen Duddi Haribabu, Prashant Singh Ahluwalia, Ryan Wang Gao, Jong-Chin Lin, Lea Vega Romero, Balaji Ramasubramaniam, Adeel Jamil Siddiqui, Onur Tuna
  • Publication number: 20220405077
    Abstract: Technologies related to predicting whether a requested change (deployment) in a cloud computing environment will fail are described herein. An exposomic feature value is computed based upon a time series of risk values, where the risk values represent risk of failure over several historic time intervals. A probabilistic model computes a likelihood that the requested deployment will fail during implementation of the requested deployment based upon the exposomic feature value and a contextual feature value, and a notification is transmitted to a computing device of a change manager to allow the change manager to take remedial action.
    Type: Application
    Filed: June 21, 2021
    Publication date: December 22, 2022
    Inventors: Xinjian XUE, Bin PAN, Naveen Duddi HARIBABU, Prashant Singh AHLUWALIA, Ryan Wang GAO, Jong-Chin LIN, Lea VEGA ROMERO, Balaji RAMASUBRAMANIAM, Adeel Jamil SIDDIQUI, Onur TUNA