Patents by Inventor Aaron Kaminsky

Aaron Kaminsky 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).

  • System and algorithms for fast and scalable data access to high dimensionality with sparse data
    Patent number: 12675481
    Abstract: A method and system(s) for processing queries to sparsely populated datasets. The method includes (i) receiving a query from a client system, (ii) determining, based at least in part on the query, a plurality of partitions of a hypercube that are expected to comprise information used in generating a response for the query, (iii) communicating a set of requests to a data source storing the hypercube, the set of requests comprising one or more requests corresponding to the plurality of partitions of the hypercube, (iv) obtaining, from the data source, a set of results to the set of requests, the set of results comprising data stored in the plurality of partitions of the hypercube, (v) determining a plurality of virtual objects for the set of results, (vi) combining the plurality of virtual objects into a response to the query, and (vii) providing the response to the query.
    Type: Grant
    Filed: January 8, 2025
    Date of Patent: July 7, 2026
    Assignee: Workday, Inc.
    Inventors: Ragy Eleish, Aaron Kaminsky, Yunfeng Fei, Yuh-Ming Shyy, Ramabrahmam Venkata Velury, Ashish Patel, Christof Bornhoevd
  • SYSTEM AND ALGORITHMS FOR FAST AND SCALABLE DATA ACCESS TO HIGH DIMENSIONALITY WITH SPARSE DATA
    Publication number: 20250147960
    Abstract: The present application discloses a method, system, and computer system for processing queries to sparsely populated datasets. The method includes (i) receiving a query from a client system, (ii) determining, based at least in part on the query, a plurality of partitions of a hypercube that are expected to comprise information used in generating a response for the query, (iii) communicating a set of requests to a data source storing the hypercube, the set of requests comprising one or more requests corresponding to the plurality of partitions of the hypercube, (iv) obtaining, from the data source, a set of results to the set of requests, the set of results comprising data stored in the plurality of partitions of the hypercube, (v) determining a plurality of virtual objects for the set of results, (vi) combining the plurality of virtual objects into a response to the query, and (vii) providing, to the client system, the response to the query.
    Type: Application
    Filed: January 8, 2025
    Publication date: May 8, 2025
    Inventors: Ragy Eleish, Aaron Kaminsky, Yunfeng Fei, Yuh-Ming Shyy, Ramabrahmam Venkata Velury, Ashish Patel, Christof Bornhoevd
  • System and algorithms for fast and scalable data access to high dimensionality with sparse data
    Patent number: 12229133
    Abstract: The present application discloses a method, system, and computer system for processing queries to sparsely populated datasets. The method includes (i) receiving a query from a client system, (ii) determining, based at least in part on the query, a plurality of partitions of a hypercube that are expected to comprise information used in generating a response for the query, (iii) communicating a set of requests to a data source storing the hypercube, the set of requests comprising one or more requests corresponding to the plurality of partitions of the hypercube, (iv) obtaining, from the data source, a set of results to the set of requests, the set of results comprising data stored in the plurality of partitions of the hypercube, (v) determining a plurality of virtual objects for the set of results, (vi) combining the plurality of virtual objects into a response to the query, and (vii) providing, to the client system, the response to the query.
    Type: Grant
    Filed: March 17, 2023
    Date of Patent: February 18, 2025
    Assignee: Workday, Inc.
    Inventors: Ragy Eleish, Aaron Kaminsky, Yunfeng Fei, Yuh-Ming Shyy, Ramabrahmam Venkata Velury, Ashish Patel, Christof Bornhoevd