Patents by Inventor Shehzad Qureshi

Shehzad Qureshi 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).

  • Using specified performance attributes to configure machine learning pipepline stages for an ETL job
    Patent number: 11941016
    Abstract: Specified performance attributes may be used to configure machine learning transformations for ETL jobs. Performance attributes for a machine learning pipeline that applies a model to as part of a transformation for an ETL job may be used to configure a parameter in a stage of the machine learning pipeline. The configured stage may then be used when training the model. The trained machine learning pipeline may then be applied as part of a transformation operation included in an ETL job performed by the ETL system.
    Type: Grant
    Filed: March 4, 2022
    Date of Patent: March 26, 2024
    Assignee: Amazon Technologies, Inc.
    Inventors: Timothy Jones, Andrew Borthwick, Sergei Dobroshinsky, Shehzad Qureshi, Stephen Michael Ash, Pedrito Uriah Maynard-Zhang, Chethan Kommaranahalli Rudramuni, Abhishek Sharma, Juliana Saussy, Adam Lawrence Joseph Heinermann, Alaykumar Navinchandra Desai, Mehul A. Shah, Mehul Y. Shah, Anurag Windlass Gupta, Prajakta Datta Damle
  • USING SPECIFIED PERFORMANCE ATTRIBUTES TO CONFIGURE MACHINE LEARNING PIPEPLINE STAGES FOR AN ETL JOB
    Publication number: 20220261413
    Abstract: Specified performance attributes may be used to configure machine learning transformations for ETL jobs. Performance attributes for a machine learning pipeline that applies a model to as part of a transformation for an ETL job may be used to configure a parameter in a stage of the machine learning pipeline. The configured stage may then be used when training the model. The trained machine learning pipeline may then be applied as part of a transformation operation included in an ETL job performed by the ETL system.
    Type: Application
    Filed: March 4, 2022
    Publication date: August 18, 2022
    Applicant: Amazon Technologies, Inc.
    Inventors: Timothy Jones, Andrew Borthwick, Sergei Dobroshinsky, Shehzad Qureshi, Stephen Michael Ash, Pedrito Uriah Maynard-Zhang, Chethan Kommaranahalli Rudramuni, Abhishek Sharma, Juliana Saussy, Adam Lawrence Joseph Heinermann, Alaykumar Navinchandra Desai, Mehul A. Shah, Mehul Y. Shah, Anurag Windlass Gupta, Prajakta Datta Damle
  • Using specified performance attributes to configure machine learning pipeline stages for an ETL job
    Patent number: 11269911
    Abstract: Specified performance attributes may be used to configure machine learning transformations for ETL jobs. Performance attributes for a machine learning pipeline that applies a model to as part of a transformation for an ETL job may be used to configure a parameter in a stage of the machine learning pipeline. The configured stage may then be used when training the model. The trained machine learning pipeline may then be applied as part of a transformation operation included in an ETL job performed by the ETL system.
    Type: Grant
    Filed: November 23, 2018
    Date of Patent: March 8, 2022
    Assignee: Amazon Technologies, Inc.
    Inventors: Timothy Jones, Andrew Borthwick, Sergei Dobroshinsky, Shehzad Qureshi, Stephen Michael Ash, Pedrito Uriah Maynard-Zhang, Chethan Kommaranahalli Rudramuni, Abhishek Sharma, Juliana Saussy, Adam Lawrence Joseph Heinermann, Alaykumar Navinchandra Desai, Mehul A. Shah, Mehul Y. Shah, Anurag Windlass Gupta, Prajakta Datta Damle
  • Intersection-based dynamic blocking
    Patent number: 10599614
    Abstract: Block size reduction iterations are performed on a plurality of blocks of records until a block size criterion is met. An iteration comprises identifying, from a first collection of blocks, using one or more pivot operations, a set of combinations of oversized blocks such that at least one record belongs to all blocks of a combination. A new block comprising records that are members of each block of a first combination of the set is included in a second collection of blocks to be examined in a subsequent iteration. On at least one block created in an iteration, analysis operations are performed.
    Type: Grant
    Filed: January 2, 2018
    Date of Patent: March 24, 2020
    Assignee: Amazon Technologies, Inc.
    Inventors: Andrew Borthwick, Tianyi Lu, Shehzad Qureshi, Timothy Jones