Patents by Inventor Avnish Kumar

Avnish Kumar 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: 20250095323
    Abstract: A method including receiving a first set of one or more street level images of houses into a Machine Learned Model trained with a second set of street level images with one or more exterior features of the houses labeled, identifying the one or more exterior features in the first set of street level images by way of the Machine Learned Model, and quantifying and outputting the counts and/or two-dimensional areas for each of the identified exterior features in the first set of one or more street level images is described. Non-transitory, computer-readable storage media having instructions for executing the method steps by one or more processors as well as computer or computer systems capable of performing the method steps are also described.
    Type: Application
    Filed: September 15, 2023
    Publication date: March 20, 2025
    Inventors: Sivakumaran Somasundaram, Ali Salman, Avnish Kumar, Ian Michael Scott, Todd Alan Tomalak
  • Publication number: 20250095324
    Abstract: A method including receiving a first set of one or more street level images of houses into a Machine Learned Model trained with a second set of street level images with one or more exterior features of the houses labeled, identifying the one or more exterior features in the first set of street level images by way of the Machine Learned Model, and quantifying and outputting the counts and/or two-dimensional areas for each of the identified exterior features in the first set of one or more street level images is described. Non-transitory, computer-readable storage media having instructions for executing the method steps by one or more processors as well as computer or computer systems capable of performing the method steps are also described.
    Type: Application
    Filed: September 15, 2023
    Publication date: March 20, 2025
    Inventors: Sivakumaran Somasundaram, Ali Salman, Avnish Kumar, Ian Michael Scott
  • Publication number: 20250095165
    Abstract: A method including receiving a first set of one or more street level images of houses into a Machine Learned Model trained with a second set of street level images with one or more exterior features of the houses labeled, identifying the one or more exterior features in the first set of street level images by way of the Machine Learned Model, and quantifying and outputting the counts and/or two-dimensional areas for each of the identified exterior features in the first set of one or more street level images is described. Non-transitory, computer-readable storage media having instructions for executing the method steps by one or more processors as well as computer or computer systems capable of performing the method steps are also described.
    Type: Application
    Filed: September 15, 2023
    Publication date: March 20, 2025
    Inventors: Sivakumaran Somasundaram, Ali Salman, Avnish Kumar, Ian Michael Scott, Todd Alan Tomalak
  • Publication number: 20250095330
    Abstract: A method including receiving a first set of one or more street level images of houses into a Machine Learned Model trained with a second set of street level images with one or more exterior features of the houses labeled, identifying the one or more exterior features in the first set of street level images by way of the Machine Learned Model, and quantifying and outputting the counts and/or two-dimensional areas for each of the identified exterior features in the first set of one or more street level images is described. Non-transitory, computer-readable storage media having instructions for executing the method steps by one or more processors as well as computer or computer systems capable of performing the method steps are also described.
    Type: Application
    Filed: November 19, 2024
    Publication date: March 20, 2025
    Inventors: Sivakumaran Somasundaram, Ali Salman, Avnish Kumar, Ian Michael Scott
  • Patent number: 12254660
    Abstract: A method including receiving a first set of one or more street level images of houses into a Machine Learned Model trained with a second set of street level images with one or more exterior features of the houses labeled, identifying the one or more exterior features in the first set of street level images by way of the Machine Learned Model, and quantifying and outputting the counts and/or two-dimensional areas for each of the identified exterior features in the first set of one or more street level images is described. Non-transitory, computer-readable storage media having instructions for executing the method steps by one or more processors as well as computer or computer systems capable of performing the method steps are also described.
    Type: Grant
    Filed: September 15, 2023
    Date of Patent: March 18, 2025
    Assignee: Metrostudy Inc.
    Inventors: Sivakumaran Somasundaram, Ali Salman, Avnish Kumar, Ian Michael Scott, Todd Alan Tomalak
  • Patent number: 12254661
    Abstract: A method including receiving a first set of one or more street level images of houses into a Machine Learned Model trained with a second set of street level images with one or more exterior features of the houses labeled, identifying the one or more exterior features in the first set of street level images by way of the Machine Learned Model, and quantifying and outputting the counts and/or two-dimensional areas for each of the identified exterior features in the first set of one or more street level images is described. Non-transitory, computer-readable storage media having instructions for executing the method steps by one or more processors as well as computer or computer systems capable of performing the method steps are also described.
    Type: Grant
    Filed: September 15, 2023
    Date of Patent: March 18, 2025
    Assignee: Metrostudy Inc.
    Inventors: Sivakumaran Somasundaram, Ali Salman, Avnish Kumar, Ian Michael Scott
  • Patent number: 12154308
    Abstract: A method including receiving a first set of one or more street level images of houses into a Machine Learned Model trained with a second set of street level images with one or more exterior features of the houses labeled, identifying the one or more exterior features in the first set of street level images by way of the Machine Learned Model, and quantifying and outputting the counts and/or two-dimensional areas for each of the identified exterior features in the first set of one or more street level images is described. Non-transitory, computer-readable storage media having instructions for executing the method steps by one or more processors as well as computer or computer systems capable of performing the method steps are also described.
    Type: Grant
    Filed: September 15, 2023
    Date of Patent: November 26, 2024
    Inventors: Sivakumaran Somasundaram, Ali Salman, Avnish Kumar, Ian Michael Scott
  • Publication number: 20240005348
    Abstract: The disclosure features a method which includes inputting or receiving information on one or more features of a plurality of residential properties and prices of the residential properties including a marketed price, a listing price, and a closing price, providing the information to a Machine Learning Algorithm to determine the relationship between the one or more features and the prices of the residential properties to create a Machine Learned Model, inputting or receiving information on one or more features of a new residential property into the Machine Learned Model, and predicting a base price of the new residential property from the Machine Learned Model based on the one or more features of the new residential property. The disclosure also features one or more non-transitory, computer-readable storage media storing instructions capable of performing the method and a computer or computer system capable of performing the method.
    Type: Application
    Filed: June 30, 2022
    Publication date: January 4, 2024
    Inventors: Corentin Guillo, Sivakumaran Somasundaram, Pablo Lopez Santori, Ali Salman, Gordon Campbell Wells, Avnish Kumar
  • Publication number: 20230370867
    Abstract: Present disclosure generally relates to data analytics in wireless networks, more particularly relates to systems and methods for optimizing supply demand in telecommunication network. System may prepare data for optimization using raw telecom data. Further, the system may build quadratic optimization objective function by reading index table (cell—grid information). System may build quadratic program inequality constraints, and prepare right hand side of constraints for all mentioned constraints maintaining the index. Thereafter, the system may execute optimizer and find the optimal solution ensuring hyper-parameter tuning, and calculate focal point of each cell using cell-grid allocation vector. The system may read the optimal solution from optimization process, and estimate electronic tilt values (i.e., Remote Electrical Tilt (RET)) ensuring the business guidelines. Thereafter, the system may use line of sight method to get inclination value (optimal tilt value) of cell from the focal point on the ground.
    Type: Application
    Filed: August 1, 2022
    Publication date: November 16, 2023
    Inventors: Shailesh KUMAR, Anil MITTAL, Prateek Kumar JAIN, Avnish KUMAR
  • Publication number: 20230354045
    Abstract: Present disclosure generally relate to wireless networks, more particularly relates to systems and methods for determining spatial clusters in a network to enable connected community of telecommunication cellular towers. The system may prepare cell data using one or more circle data, city data, cell Identity (ID) data, latitude data, longitude data, azimuth data, and height data. System may compute geohash based on creating geohash neighbours and geohash bounding box data and compute sectors of the telecommunication towers. Further, the system may compute sector affinity of the telecommunication towers and perform clustering of the telecommunication towers.
    Type: Application
    Filed: July 29, 2022
    Publication date: November 2, 2023
    Inventors: Shailesh KUMAR, Anil MITTAL, Prateek Kumar JAIN, Avnish KUMAR
  • Publication number: 20230289370
    Abstract: The present disclosure relates to a system and a method for processing distributed data files. The processor executes instructions to receive a set of instructions from a primary device, wherein the set of instructions comprises verification rules, validators, primary transformers and structure query transformers; generate processed data files by processing the distributed data files. The distributed data files are processed by performing at least one of: executing one of the verification rules, the validators and the primary transformers on the distributed data files; and transforming the distributed data files by executing the structure query transformers. The execution of the structured query transformers comprises steps of generating a dependency graph based upon dependencies between the structure query transformers; and determining a sequence of execution of the structured query transformers based upon the dependency graph; and transfer the processed data files to a data warehouse.
    Type: Application
    Filed: May 23, 2023
    Publication date: September 14, 2023
    Inventors: AVNISH KUMAR RASTOGI, NITIN NARANG, MOHAMMAD AJMAL
  • Patent number: 11727009
    Abstract: Disclosed is a method and system for processing skewed datasets. The processor 202 is configured to capture a broadcast size of non-skewed datasets to be loaded onto a memory associated with one or more nodes in a distributed system. The skewed dataset is identified from two or more datasets to be joined. Each of the non-skewed dataset is divided into a plurality of non-skewed data chunks at the node and each of the non-skewed data chunk is broadcasted to one or more nodes having the skewed dataset. The joining operation is then performed between each of the skewed dataset and the non-skewed data chunk till all the non-skewed data chunks are consumed in the join operation. Resultant joined dataset is then collected as a single joined dataset from the nodes involved in the joining operation.
    Type: Grant
    Filed: September 29, 2020
    Date of Patent: August 15, 2023
    Inventor: Avnish Kumar Rastogi
  • Patent number: 11693884
    Abstract: The present disclosure relates to a system and a method for processing distributed data files. The processor executes instructions to receive a set of instructions from a primary device, wherein the set of instructions comprises verification rules, validators, primary transformers and structure query transformers; generate processed data files by processing the distributed data files. The distributed data files are processed by performing at least one of: executing one of the verification rules, the validators and the primary transformers on the distributed data files; and transforming the distributed data files by executing the structure query transformers. The execution of the structured query transformers comprises steps of generating a dependency graph based upon dependencies between the structure query transformers; and determining a sequence of execution of the structured query transformers based upon the dependency graph; and transfer the processed data files to a data warehouse.
    Type: Grant
    Filed: March 4, 2020
    Date of Patent: July 4, 2023
    Assignee: HCL TECHNOLOGIES LIMITED
    Inventors: Avnish Kumar Rastogi, Nitin Narang, Mohammad Ajmal
  • Patent number: 11615094
    Abstract: Disclosed is a method and system for joining datasets in a distributed computing environment. The system comprises a memory 206 and a processor 202. The processor 202 identifies a skewed dataset from two or more datasets to be joined. The processor 202 identifies a replication parameter from a configuration file. The processor 202 then assigns a randomly assigned machine number to each chunk of the skewed dataset owned by the nodes/machines involved in the join operation. The processor 202 forms copies of the non-skewed dataset equal to the replication parameter and adds the copy number to each sample of the copy of the non-skewed dataset formed. Further, the processor 202 merges each non-skewed dataset into the final copy of the non-skewed dataset, forming a single non skewed dataset. The processor 202 then repeats these steps for all the non-skewed datasets involved in the join operation resulting in generation of merged copies of all the non-skewed datasets and then performs the joining operation.
    Type: Grant
    Filed: August 12, 2020
    Date of Patent: March 28, 2023
    Assignee: HCL TECHNOLOGIES LIMITED
    Inventor: Avnish Kumar Rastogi
  • Patent number: 11366744
    Abstract: Systems, methods and computer program products are described herein that can be used to help achieve a safe rollout of software in a production datacenter environment. In accordance with certain embodiments, cloud services requests from certain users of a cloud services system (e.g., users that are authorized to receive cloud services via computing devices running test versions of infrastructure software) are dynamically matched to clusters (groups of commonly-managed computing devices called nodes) that are capable of providing the requested services on nodes running test versions of infrastructure software. Within such clusters, the requested services are provided to the users on a subset of cluster nodes that run a test version of an infrastructure software component, while the remaining cluster nodes are not running the particular test version.
    Type: Grant
    Filed: September 29, 2017
    Date of Patent: June 21, 2022
    Assignee: MICROSOFT TECHNOLOGY LICENSING, LLC
    Inventors: Reza Sherafat Kazemzadeh, Harsh Gupta, Binit R. Mishra, Yevgeniy Olegovich Razuvayev, Muhammad Usman Sharif, Li-Fen Wu, Cristina del Amo Casado, Avnish Kumar Chhabra, Hariharan Jayaraman, Li Xiong, Abhishek Singh
  • Publication number: 20220100752
    Abstract: Disclosed is a method and system for processing skewed datasets. The processor 202 is configured to capture a broadcast size of non-skewed datasets to be loaded onto a memory associated with one or more nodes in a distributed system. The skewed dataset is identified from two or more datasets to be joined. Each of the non-skewed dataset is divided into a plurality of non-skewed data chunks at the node and each of the non-skewed data chunk is broadcasted to one or more nodes having the skewed dataset. The joining operation is then performed between each of the skewed dataset and the non-skewed data chunk till all the non-skewed data chunks are consumed in the join operation. Resultant joined dataset is then collected as a single joined dataset from the nodes involved in the joining operation.
    Type: Application
    Filed: September 29, 2020
    Publication date: March 31, 2022
    Inventor: Avnish Kumar RASTOGI
  • Publication number: 20220050845
    Abstract: Disclosed is a method and system for joining datasets in a distributed computing environment. The system comprises a memory 206 and a processor 202. The processor 202 identifies a skewed dataset from two or more datasets to be joined. The processor 202 identifies a replication parameter from a configuration file. The processor 202 then assigns a randomly assigned machine number to each chunk of the skewed dataset owned by the nodes/machines involved in the join operation. The processor 202 forms copies of the non-skewed dataset equal to the replication parameter and adds the copy number to each sample of the copy of the non-skewed dataset formed. Further, the processor 202 merges each non-skewed dataset into the final copy of the non-skewed dataset, forming a single non skewed dataset. The processor 202 then repeats these steps for all the non-skewed datasets involved in the join operation resulting in generation of merged copies of all the non-skewed datasets and then performs the joining operation.
    Type: Application
    Filed: August 12, 2020
    Publication date: February 17, 2022
    Applicant: HCL TECHNOLOGIES LIMITED
    Inventor: Avnish Kumar RASTOGI
  • Patent number: 11126642
    Abstract: Disclosed method for generating synthetic data for minority classes in a very large dataset comprises grouping samples stored on several devices, into different groups. A pivot is identified to be used as a reference for grouping the samples into bins. The samples are assigned to a bin, based on a closest pivot. The samples are regrouped into different groups, based on identities of the bins, and each of the groups is distributed to the several devices. Samples belonging to majority class and minority classes for which synthetic data is not being generated are removed from each of the different groups. Samples of each of these groups are arranged in different M-Trees to facilitate identification of K-nearest neighbours for each sample within each of the different groups to generate K pairs of nearest neighbours. Finally, synthetic samples are generated for the K pairs of nearest neighbours by creating random samples.
    Type: Grant
    Filed: July 29, 2019
    Date of Patent: September 21, 2021
    Inventors: Avnish Kumar Rastogi, Nitin Narang, Mohammad Ajmal
  • Publication number: 20210279259
    Abstract: The present disclosure relates to a system and a method for processing distributed data files. The processor executes instructions to receive a set of instructions from a primary device, wherein the set of instructions comprises verification rules, validators, primary transformers and structure query transformers; generate processed data files by processing the distributed data files. The distributed data files are processed by performing at least one of: executing one of the verification rules, the validators and the primary transformers on the distributed data files; and transforming the distributed data files by executing the structure query transformers. The execution of the structured query transformers comprises steps of generating a dependency graph based upon dependencies between the structure query transformers; and determining a sequence of execution of the structured query transformers based upon the dependency graph; and transfer the processed data files to a data warehouse.
    Type: Application
    Filed: March 4, 2020
    Publication date: September 9, 2021
    Applicant: HCL TECHNOLOGIES LIMITED
    Inventors: Avnish Kumar RASTOGI, Nitin NARANG, Mohammad AJMAL
  • Patent number: 11038947
    Abstract: Methods, systems, apparatuses, and computer program products are provided that enable the automated deployment of microservices to a network-accessible server set. The automated deployment may be based on constraint(s) that are specified by a declarative deployment model that is associated with the microservice to be deployed. For example, a centralized deployment orchestrator may receive microservice(s) and their associated declarative deployment model(s). The deployment orchestrator analyzes the declarative deployment model(s) and determines which microservice(s) are to be deployed based on the constraint(s) specified by the declarative deployment model(s). The foregoing techniques advantageously determine when to deploy microservice(s), while also minimizing human intervention typically required to deploy microservice(s).
    Type: Grant
    Filed: April 21, 2017
    Date of Patent: June 15, 2021
    Assignee: MICROSOFT TECHNOLOGY LICENSING, LLC
    Inventors: Yue Zhao, Siddharth Verma, Huaming Huang, Ash Beitz, Arbab Amjad, Muhammad Usman Sharif, Abhishek Singh, Avnish Kumar Chhabra