Patents by Inventor Stuart A. Siegel

Stuart A. Siegel 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: 20230194756
    Abstract: A method, system, and computer program product for resource management are described. The method includes selecting trouble regions within the service area, generating clustered regions, and training a trouble forecast model for the trouble regions for each type of damage, the training for each trouble region using training data from every trouble region within the clustered region associated with the trouble region. The method also includes applying the trouble forecast model for each trouble region within the service area for each type of damage, determining a trouble forecast for the service area for each type of damage based on the trouble forecast for each of the trouble regions within the service area, and determining a job forecast for the service area based on the trouble forecast for the service area, wherein the managing resources is based on the job forecast for the service area.
    Type: Application
    Filed: February 10, 2023
    Publication date: June 22, 2023
    Applicant: Utopus Insights, Inc.
    Inventors: Fook-Luen Heng, Zhiguo Li, Stuart A. Siegel, Amith Singhee, Haijing Wang
  • Patent number: 11598900
    Abstract: A method, system, and computer program product for resource management are described. The method includes selecting trouble regions within the service area, generating clustered regions, and training a trouble forecast model for the trouble regions for each type of damage, the training for each trouble region using training data from every trouble region within the clustered region associated with the trouble region. The method also includes applying the trouble forecast model for each trouble region within the service area for each type of damage, determining a trouble forecast for the service area for each type of damage based on the trouble forecast for each of the trouble regions within the service area, and determining a job forecast for the service area based on the trouble forecast for the service area, wherein the managing resources is based on the job forecast for the service area.
    Type: Grant
    Filed: April 6, 2021
    Date of Patent: March 7, 2023
    Assignee: Utopus Insights, Inc.
    Inventors: Fook-Luen Heng, Zhiguo Li, Stuart A. Siegel, Amith Singhee, Haijing Wang
  • Publication number: 20210223434
    Abstract: A method, system, and computer program product for resource management are described. The method includes selecting trouble regions within the service area, generating clustered regions, and training a trouble forecast model for the trouble regions for each type of damage, the training for each trouble region using training data from every trouble region within the clustered region associated with the trouble region. The method also includes applying the trouble forecast model for each trouble region within the service area for each type of damage, determining a trouble forecast for the service area for each type of damage based on the trouble forecast for each of the trouble regions within the service area, and determining a job forecast for the service area based on the trouble forecast for the service area, wherein the managing resources is based on the job forecast for the service area.
    Type: Application
    Filed: April 6, 2021
    Publication date: July 22, 2021
    Applicant: Utopus Insights, Inc.
    Inventors: Fook-Luen Heng, Zhiguo Li, Stuart A. Siegel, Amith Singhee, Haijing Wang
  • Patent number: 11048021
    Abstract: A method, system, and computer program product for resource management are described. The method includes selecting trouble regions within the service area, generating clustered regions, and training a trouble forecast model for the trouble regions for each type of damage, the training for each trouble region using training data from every trouble region within the clustered region associated with the trouble region. The method also includes applying the trouble forecast model for each trouble region within the service area for each type of damage, determining a trouble forecast for the service area for each type of damage based on the trouble forecast for each of the trouble regions within the service area, and determining a job forecast for the service area based on the trouble forecast for the service area, wherein the managing resources is based on the job forecast for the service area.
    Type: Grant
    Filed: August 20, 2019
    Date of Patent: June 29, 2021
    Assignee: Utopus Insights, Inc.
    Inventors: Fook-Luen Heng, Zhiguo Li, Stuart A. Siegel, Amith Singhee, Haijing Wang
  • Patent number: 10989838
    Abstract: A method, system, and computer program product for resource management are described. The method includes selecting trouble regions within the service area, generating clustered regions, and training a trouble forecast model for the trouble regions for each type of damage, the training for each trouble region using training data from every trouble region within the clustered region associated with the trouble region. The method also includes applying the trouble forecast model for each trouble region within the service area for each type of damage, determining a trouble forecast for the service area for each type of damage based on the trouble forecast for each of the trouble regions within the service area, and determining a job forecast for the service area based on the trouble forecast for the service area, wherein the managing resources is based on the job forecast for the service area.
    Type: Grant
    Filed: January 21, 2016
    Date of Patent: April 27, 2021
    Assignee: Utopus Insights, Inc.
    Inventors: Fook-Luen Heng, Zhiguo Li, Stuart A. Siegel, Amith Singhee, Haijing Wang
  • Publication number: 20200111020
    Abstract: A method, system, and computer program product for resource management are described. The method includes selecting trouble regions within the service area, generating clustered regions, and training a trouble forecast model for the trouble regions for each type of damage, the training for each trouble region using training data from every trouble region within the clustered region associated with the trouble region. The method also includes applying the trouble forecast model for each trouble region within the service area for each type of damage, determining a trouble forecast for the service area for each type of damage based on the trouble forecast for each of the trouble regions within the service area, and determining a job forecast for the service area based on the trouble forecast for the service area, wherein the managing resources is based on the job forecast for the service area.
    Type: Application
    Filed: August 20, 2019
    Publication date: April 9, 2020
    Inventors: Fook-Luen Heng, Zhiguo Li, Stuart A. Siegel, Amith Singhee, Haijing Wang
  • Patent number: 10387802
    Abstract: A method, system, and computer program product for resource management are described. The method includes selecting trouble regions within the service area, generating clustered regions, and training a trouble forecast model for the trouble regions for each type of damage, the training for each trouble region using training data from every trouble region within the clustered region associated with the trouble region. The method also includes applying the trouble forecast model for each trouble region within the service area for each type of damage, determining a trouble forecast for the service area for each type of damage based on the trouble forecast for each of the trouble regions within the service area, and determining a job forecast for the service area based on the trouble forecast for the service area, wherein the managing resources is based on the job forecast for the service area.
    Type: Grant
    Filed: October 7, 2016
    Date of Patent: August 20, 2019
    Assignee: Utopus Insights, Inc.
    Inventors: Fook-Luen Heng, Zhiguo Li, Stuart A. Siegel, Amith Singhee, Haijing Wang
  • Patent number: 10339107
    Abstract: Methods, systems, and computer program products for multi-level colocation and analytical processing of spatial data on MapReduce are provided herein. A method includes correlating multiple items of spatial data and multiple items of attribute data within a file system to generate multiple blocks of correlated data; colocating each of the multiple blocks of correlated data on a given node within the file system based on a data block placement policy; and clustering multiple replicas generated for each of the multiple data blocks at multiple levels of spatial granularity within the file system.
    Type: Grant
    Filed: June 8, 2015
    Date of Patent: July 2, 2019
    Assignee: International Business Machines Corporation
    Inventors: Tanveer A. Faruquie, Himanshu Gupta, Sriram Lakshminarasimhan, Sameep Mehta, Stuart A. Siegel
  • Patent number: 9600773
    Abstract: A method for detecting anomalous energy usage of building or household entities. The method applies a number of successively stringent anomaly detection techniques to isolate households that are highly suspect for having engaged in electricity theft via meter tampering. The system utilizes historical time series data of electricity usage, weather, and household characteristics (e.g., size, age, value) and provides a list of households that are worthy of a formal theft investigation. Generally, raw utility usage data, weather history data, and household characteristics are cleansed, and loaded into an analytics data mart. The data mart feeds four classes of anomaly detection algorithms developed, with each analytic producing a set of households suspected of having engaged in electricity theft. The system allows a user to select households from each list or a set based on the intersection of all individual sets.
    Type: Grant
    Filed: September 13, 2013
    Date of Patent: March 21, 2017
    Assignee: International Business Machines Corporation
    Inventors: Amit Dhurandhar, Jayant R. Kalagnanam, Stuart A. Siegel, Yada Zhu
  • Patent number: 9595006
    Abstract: A system and method for detecting anomalous energy usage of building or household entities. The method applies a number of successively stringent anomaly detection techniques to isolate households that are highly suspect for having engaged in electricity theft via meter tampering. The system utilizes historical time series data of electricity usage, weather, and household characteristics (e.g., size, age, value) and provides a list of households that are worthy of a formal theft investigation. Generally, raw utility usage data, weather history data, and household characteristics are cleansed, and loaded into an analytics data mart. The data mart feeds four classes of anomaly detection algorithms developed, with each analytic producing a set of households suspected of having engaged in electricity theft. The system allows a user to select households from each list or a set based on the intersection of all individual sets.
    Type: Grant
    Filed: June 4, 2013
    Date of Patent: March 14, 2017
    Assignee: International Business Machines Corporation
    Inventors: Amit Dhurandhar, Jayant R. Kalagnanam, Stuart A. Siegel, Yada Zhu
  • Publication number: 20170017904
    Abstract: A method, system, and computer program product for resource management are described. The method includes selecting trouble regions within the service area, generating clustered regions, and training a trouble forecast model for the trouble regions for each type of damage, the training for each trouble region using training data from every trouble region within the clustered region associated with the trouble region. The method also includes applying the trouble forecast model for each trouble region within the service area for each type of damage, determining a trouble forecast for the service area for each type of damage based on the trouble forecast for each of the trouble regions within the service area, and determining a job forecast for the service area based on the trouble forecast for the service area, wherein the managing resources is based on the job forecast for the service area.
    Type: Application
    Filed: October 7, 2016
    Publication date: January 19, 2017
    Inventors: Fook-Luen Heng, Zhiguo Li, Stuart A. Siegel, Amith Singhee, Haijing Wang
  • Patent number: 9536214
    Abstract: A method, system, and computer program product for resource management are described. The method includes selecting trouble regions within the service area, generating clustered regions, and training a trouble forecast model for the trouble regions for each type of damage, the training for each trouble region using training data from every trouble region within the clustered region associated with the trouble region. The method also includes applying the trouble forecast model for each trouble region within the service area for each type of damage, determining a trouble forecast for the service area for each type of damage based on the trouble forecast for each of the trouble regions within the service area, and determining a job forecast for the service area based on the trouble forecast for the service area, wherein the managing resources is based on the job forecast for the service area.
    Type: Grant
    Filed: March 21, 2016
    Date of Patent: January 3, 2017
    Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
    Inventors: Fook-Luen Heng, Zhiguo Li, Stuart A. Siegel, Amith Singhee, Haijing Wang
  • Publication number: 20160357775
    Abstract: Methods, systems, and computer program products for multi-level colocation and analytical processing of spatial data on MapReduce are provided herein. A method includes correlating multiple items of spatial data and multiple items of attribute data within a file system to generate multiple blocks of correlated data; colocating each of the multiple blocks of correlated data on a given node within the file system based on a data block placement policy; and clustering multiple replicas generated for each of the multiple data blocks at multiple levels of spatial granularity within the file system.
    Type: Application
    Filed: June 8, 2015
    Publication date: December 8, 2016
    Inventors: Tanveer A. Faruquie, Himanshu Gupta, Sriram Lakshminarasimhan, Sameep Mehta, Stuart A. Siegel
  • Publication number: 20160307138
    Abstract: A method, system, and computer program product for resource management are described. The method includes selecting trouble regions within the service area, generating clustered regions, and training a trouble forecast model for the trouble regions for each type of damage, the training for each trouble region using training data from every trouble region within the clustered region associated with the trouble region. The method also includes applying the trouble forecast model for each trouble region within the service area for each type of damage, determining a trouble forecast for the service area for each type of damage based on the trouble forecast for each of the trouble regions within the service area, and determining a job forecast for the service area based on the trouble forecast for the service area, wherein the managing resources is based on the job forecast for the service area.
    Type: Application
    Filed: March 21, 2016
    Publication date: October 20, 2016
    Inventors: Fook-Luen Heng, Zhiguo Li, Stuart A. Siegel, Amith Singhee, Haijing Wang
  • Publication number: 20160306075
    Abstract: A method, system, and computer program product for resource management are described. The method includes selecting trouble regions within the service area, generating clustered regions, and training a trouble forecast model for the trouble regions for each type of damage, the training for each trouble region using training data from every trouble region within the clustered region associated with the trouble region. The method also includes applying the trouble forecast model for each trouble region within the service area for each type of damage, determining a trouble forecast for the service area for each type of damage based on the trouble forecast for each of the trouble regions within the service area, and determining a job forecast for the service area based on the trouble forecast for the service area, wherein the managing resources is based on the job forecast for the service area.
    Type: Application
    Filed: January 21, 2016
    Publication date: October 20, 2016
    Inventors: Fook-Luen Heng, Zhiguo Li, Stuart A. Siegel, Amith Singhee, Haijing Wang
  • Publication number: 20140358838
    Abstract: A system and method for detecting anomalous energy usage of building or household entities. The method applies a number of successively stringent anomaly detection techniques to isolate households that are highly suspect for having engaged in electricity theft via meter tampering. The system utilizes historical time series data of electricity usage, weather, and household characteristics (e.g., size, age, value) and provides a list of households that are worthy of a formal theft investigation. Generally, raw utility usage data, weather history data, and household characteristics are cleansed, and loaded into an analytics data mart. The data mart feeds four classes of anomaly detection algorithms developed, with each analytic producing a set of households suspected of having engaged in electricity theft. The system allows a user to select households from each list or a set based on the intersection of all individual sets.
    Type: Application
    Filed: June 4, 2013
    Publication date: December 4, 2014
    Inventors: Amit Dhurandhar, Jayant R. Kalagnanam, Stuart A. Siegel, Yada Zhu
  • Publication number: 20140358839
    Abstract: A method for detecting anomalous energy usage of building or household entities. The method applies a number of successively stringent anomaly detection techniques to isolate households that are highly suspect for having engaged in electricity theft via meter tampering. The system utilizes historical time series data of electricity usage, weather, and household characteristics (e.g., size, age, value) and provides a list of households that are worthy of a formal theft investigation. Generally, raw utility usage data, weather history data, and household characteristics are cleansed, and loaded into an analytics data mart. The data mart feeds four classes of anomaly detection algorithms developed, with each analytic producing a set of households suspected of having engaged in electricity theft. The system allows a user to select households from each list or a set based on the intersection of all individual sets.
    Type: Application
    Filed: September 13, 2013
    Publication date: December 4, 2014
    Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATION
    Inventors: Amit Dhurandhar, Jayant R. Kalagnanam, Stuart A. Siegel, Yada Zhu
  • Patent number: 8670856
    Abstract: A method and system for optimizing modules of a steel manufacturing process includes a plurality of manufacturing modules for a manufacturing process. Each of the modules have a plurality of steps. The plurality of modules include at least an upstream module, a casting module, and a downstream module. Each of the plurality of modules have parameters, and include at least one variable event. The variable event is adjustable for optimization of the manufacturing process while the parameters are being maintained for each of the plurality of modules. A communication system is used for exchanging information between the modules while the manufacturing process is occurring to adjust the at least one variable event for optimizing the manufacturing process.
    Type: Grant
    Filed: June 20, 2011
    Date of Patent: March 11, 2014
    Assignee: International Business Machines Corporation
    Inventors: Andrew J. Davenport, Toshiyuki Hama, Jayant R. Kalagnanam, Chandrasekhara K. Reddy, Stuart A. Siegel
  • Patent number: 8463651
    Abstract: There are provided a system, a method and a computer program product for tracking an inventory distribution of a perishable product in a supply chain. The system receives shipment data and point of sale data for the product from every location in the supply chain. The system creates, based on the obtained shipment data and the point of sale data, a network graph that represents a flow of the product in the supply chain. The system identifies an age of unsold inventory of the product at each node of the graph based on the created graph. The system provides a notification to a user at each location that informs the age of the unsold inventory of the product at that location.
    Type: Grant
    Filed: May 27, 2011
    Date of Patent: June 11, 2013
    Assignee: International Business Machines Corporation
    Inventors: Daniel P. Connors, Markus R. Ettl, Mary E. Helander, Shubir Kapoor, Stuart A. Siegel
  • Publication number: 20120323353
    Abstract: A method and system for optimizing modules of a steel manufacturing process includes a plurality of manufacturing modules for a manufacturing process. Each of the modules have a plurality of steps. The plurality of modules include at least an upstream module, a casting module, and a downstream module. Each of the plurality of modules have parameters, and include at least one variable event. The variable event is adjustable for optimization of the manufacturing process while the parameters are being maintained for each of the plurality of modules. A communication system is used for exchanging information between the modules while the manufacturing process is occurring to adjust the at least one variable event for optimizing the manufacturing process.
    Type: Application
    Filed: June 20, 2011
    Publication date: December 20, 2012
    Applicant: International Business Machines Corporation
    Inventors: Andrew J. Davenport, Toshiyuki Hama, Jayant R. Kalagnanam, Chandrasekhara K. Reddy, Stuart A. Siegel