Patents by Inventor Roger N. Anderson

Roger N. Anderson 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: 20190370690
    Abstract: Energy Analytics Learning Machine (or EALM) system is a machine learning based, “brutally empirical” analysis system for use in optimizing the payout from one or more energy sources. EALM system optimizes exploration, production, distribution and/or consumption of an energy source while minimizing costs to the producer, transporter, refiner and/or consumer. Normalized data are processed to determine clusters of correlation in multi-dimensional space to identify a machine learned ranking of importance weights for each attribute. Predictive and prescriptive optimization on the normalized energy data is performed utilizing unique combinations of machine learning and statistical algorithm ensembles. The unstructured textual energy data are classified to correlate with optimal production to capture the dynamics of one or more energy sources of physically real or theoretically calculated systems to provide categorization results from labeled data sets to identify patterns.
    Type: Application
    Filed: August 12, 2019
    Publication date: December 5, 2019
    Inventors: ROGER N. ANDERSON, BOYI XIE, LEON L. WU, ARTHUR KRESSNER
  • Patent number: 10430725
    Abstract: Petroleum Analytics Learning Machine (or PALM) system is a machine learning based, “brutally empirical” analysis system for use in all upstream and midstream oil and gas operations. PALM system optimizes exploration, production and gathering from at least one well of oil and natural gas fields to maximize production while minimizing costs. Normalized data are processed to determine clusters of correlation in multi-dimensional space to identify a machine learned ranking of importance weights for each attribute. Predictive and prescriptive optimization on the normalized data is performed utilizing unique combinations of machine learning and statistical algorithm ensembles. The unstructured textual data are classified to correlate with optimal production to capture the dynamics of at least one or more wells of oil and natural gas fields and to provide categorization results from labeled data sets to identify patterns.
    Type: Grant
    Filed: January 18, 2017
    Date of Patent: October 1, 2019
    Assignee: AKW ANALYTICS INC.
    Inventors: Roger N. Anderson, Boyi Xie, Leon L. Wu, Arthur Kressner
  • Patent number: 10229376
    Abstract: The disclosed subject matter provides systems and methods for allocating resources within an infrastructure, such as an electrical grid, in response to changes to inputs and output demands on the infrastructure, such as energy sources and sinks.
    Type: Grant
    Filed: July 12, 2016
    Date of Patent: March 12, 2019
    Assignees: Calm Energy Inc., The Trustees of Columbia University in the City of New York
    Inventors: Roger N. Anderson, Albert Boulanger, John A. Johnson
  • Publication number: 20170364795
    Abstract: Petroleum Analytics Learning Machine (or PALM) system is a machine learning based, “brutally empirical” analysis system for use in all upstream and midstream oil and gas operations. PALM system optimizes exploration, production and gathering from at least one well of oil and natural gas fields to maximize production while minimizing costs. Normalized data are processed to determine clusters of correlation in multi-dimensional space to identify a machine learned ranking of importance weights for each attribute. Predictive and prescriptive optimization on the normalized data is performed utilizing unique combinations of machine learning and statistical algorithm ensembles. The unstructured textual data are classified to correlate with optimal production to capture the dynamics of at least one or more wells of oil and natural gas fields and to provide categorization results from labeled data sets to identify patterns.
    Type: Application
    Filed: January 18, 2017
    Publication date: December 21, 2017
    Inventors: ROGER N. ANDERSON, BOYI XIE, LEON L. WU, ARTHUR KRESSNER
  • Publication number: 20170244006
    Abstract: In some embodiments, an inline substrate processing tool may include a substrate carrier having a plurality of slots configured to retain a plurality of substrates parallel to each other when disposed in the slots, a first substrate processing module and a second substrate processing module disposed in a linear arrangement, wherein each substrate processing module includes an enclosure and a track that supports the substrate carrier and provides a path for the substrate carrier to move linearly through the first and second substrate processing modules, and a first gas cap disposed between the first and second substrate processing modules, wherein the first gas cap includes a first process gas conduit to provide a first process gas to the first substrate processing module, and a second process gas conduit to provide a second process gas to the second substrate processing module.
    Type: Application
    Filed: September 1, 2015
    Publication date: August 24, 2017
    Inventors: BRIAN H. BURROWS, NILESH BAGUL, SUMEDH ACHARYA, BAHUBALI UPADHYE, LANCE A. SCUDDER, ROGER N. ANDERSON
  • Publication number: 20170011320
    Abstract: The disclosed subject matter provides systems and methods for allocating resources within an infrastructure, such as an electrical grid, in response to changes to inputs and output demands on the infrastructure, such as energy sources and sinks.
    Type: Application
    Filed: July 12, 2016
    Publication date: January 12, 2017
    Inventors: Roger N. Anderson, Albert Boulanger, John A. Johnson
  • Publication number: 20160348240
    Abstract: Embodiments described herein generally relate to a batch processing chamber. The batch processing chamber includes a lid, a chamber wall and a bottom that define a processing region. A cassette including a stack of susceptors for supporting substrates is disposed in the processing region. The edge of the cassette is coupled to a plurality of shafts and the shafts are coupled to a rotor. During operation, the rotor rotates the cassette to improve deposition uniformity. A heating element is disposed on the chamber wall and a plurality of gas inlets is disposed through the heating element on the chamber wall. Each gas inlet is substantially perpendicular to the chamber wall.
    Type: Application
    Filed: January 6, 2015
    Publication date: December 1, 2016
    Inventors: Brian H. BURROWS, Lance A. SCUDDER, Kashif MAQSOOD, Roger N. ANDERSON, Sumedh Dattatraya ACHARYA
  • Publication number: 20160306903
    Abstract: Techniques for predicting a failure metric of a physical system using a semiparametric model, including providing raw data representative of the physical system, to identify a set of units at risk in the physical system, a set of times of treatment corresponding to a event of at least one unit in the set of units, and an index-set of the at least one unit for which a event has occurred. A parametric and a nonparametric component of the semiparametric model are estimated and a hazard rate is predicted at a given time with the semiparametric model.
    Type: Application
    Filed: October 7, 2013
    Publication date: October 20, 2016
    Inventors: Timothy Teravainen, Leon L. Wu, Roger N. Anderson, Albert Boulanger
  • Patent number: 9395707
    Abstract: The disclosed subject matter provides systems and methods for allocating resources within an infrastructure, such as an electrical grid, in response to changes to inputs and output demands on the infrastructure, such as energy sources and sinks.
    Type: Grant
    Filed: August 19, 2011
    Date of Patent: July 19, 2016
    Assignees: Calm Energy Inc., The Trustees of Columbia University in the City of New York
    Inventors: Roger N. Anderson, Albert Boulanger, John A. Johnson
  • Publication number: 20150317589
    Abstract: Techniques for determining forecast information for a resource using learning algorithms are disclosed. The techniques can include an ensemble of machine learning algorithms. The techniques can also use latent states to generate training data. The techniques can identify actions for managing the resource based on the forecast information. The resource can include energy usage in buildings, distribution facilities, and resources such as Electric Delivery Vehicles. The resource can also include forecasting package volume for businesses.
    Type: Application
    Filed: May 8, 2015
    Publication date: November 5, 2015
    Inventors: Roger N. Anderson, Albert Boulanger, Leon L. Wu, Viabhav Bhandari, Somnath Sarkar, Ashish Gagneja
  • Publication number: 20150178865
    Abstract: Techniques for managing one or more buildings, including collecting historical building data, real-time building data, historical exogenous data, and real-time exogenous data and receiving the collected data at an adaptive stochastic controller. The adaptive stochastic controller can generate at least one predicted condition with a predictive model. The adaptive stochastic controller can generate one or more executable recommendations based on at least the predicted conditions and one or more performance measurements corresponding to the executable recommendations.
    Type: Application
    Filed: July 25, 2014
    Publication date: June 25, 2015
    Applicant: The Trustees of Columbia University in the City of New York
    Inventors: Roger N. Anderson, Albert Boulanger, Vaibhav Bhandari, Eugene Boniberger, Ashish Gagneja, John Gilbert, Arthur Kressner, Ashwath Rajan, David Solomon, Jessica Forde, Leon L. Wu, Vivek Rathod, Kevin Morenski, Hooshmand Shokri
  • Publication number: 20150100284
    Abstract: Techniques for predicting a failure metric of a physical system using a semiparametric model, including providing raw data representative of the physical system, to identify a set of units at risk in the physical system, a set of times of treatment corresponding to a event of at least one unit in the set of units, and an index-set of the at least one unit for which a event has occurred. A parametric and a nonparametric component of the semiparametric model are estimated and a hazard rate is predicted at a given time with the semiparametric model.
    Type: Application
    Filed: October 7, 2013
    Publication date: April 9, 2015
    Inventors: Timothy Teravainen, Leon L. Wu, Roger N. Anderson, Albert Boulanger
  • Publication number: 20140249876
    Abstract: Techniques for managing one or more buildings, including collecting historical building data, real-time building data, historical exogenous data, and real-time exogenous data and receiving the collected data at an adaptive stochastic controller. The adaptive stochastic controller can generate at least one predicted condition with a predictive model. The adaptive stochastic controller can generate one or more executable recommendations based on at least the predicted conditions and one or more performance measurements corresponding to the executable recommendations.
    Type: Application
    Filed: March 10, 2014
    Publication date: September 4, 2014
    Inventors: Leon L. Wu, Albert Boulanger, Roger N. Anderson, Eugene M. Boniberger, Arthur A. Kressner, John J. Gilbert
  • Publication number: 20140163759
    Abstract: A system and method for monitoring status of an electrical grid and one or more building subsystems. The system includes sensors in communication with an electrical grid, buildings that provide data related to the building subsystems, and a digital building operating system that includes a processor that performs instructions to process the data, identify the status of the electrical grid and the building subsystem, predict one or more events based on the data, and provide recommendations to the buildings such as how to prevent the bad event.
    Type: Application
    Filed: December 20, 2013
    Publication date: June 12, 2014
    Applicant: THE TRUSTEES OF COLUMBIA UNIVERSITY IN THE CITY OF NEW YORK
    Inventors: Roger N. ANDERSON, Arthur A. KRESSNER, John J. GILBERT, III, Eugene M. BONIBERGER
  • Patent number: 8751421
    Abstract: A machine learning system for ranking a collection of filtered propensity to failure metrics of like components within an electrical grid that includes a raw data assembly to provide raw data representative of the like components within the electrical grid; (b) a data processor, operatively coupled to the raw data assembly, to convert the raw data to more uniform data via one or more data processing techniques; (c) a database, operatively coupled to the data processor, to store the more uniform data; (d) a machine learning engine, operatively coupled to the database, to provide a collection of propensity to failure metrics for the like components; (e) an evaluation engine, operatively coupled to the machine learning engine, to detect and remove non-complying metrics from the collection of propensity to failure metrics and to provide the collection of filtered propensity to failure metrics; and (f) a decision support application, operatively coupled to the evaluation engine, configured to display a ranking of
    Type: Grant
    Filed: January 15, 2013
    Date of Patent: June 10, 2014
    Assignees: The Trustees of Columbia University in the city of New York, Consolidated Edison Company of New York
    Inventors: Roger N. Anderson, Albert Boulanger, Cynthia Rudin, David Waltz, Ansaf Salleb-Aouissi, Maggie Chow, Haimonti Dutta, Phil Gross, Huang Bert, Steve Ierome, Delfina Isaac, Arthur Kressner, Rebecca J. Passonneau, Axinia Radeva, Leon L. Wu, Peter Hofmann, Frank Dougherty
  • Publication number: 20140156031
    Abstract: Techniques for generating a dynamic treatment control policy for a cyber-physical system having one or more components, including a data collector for collecting data representative of the cyber-physical system, and adaptive stochastic controller including one or more models for generating a predicted value corresponding to available actions based on an objective function, and an approximate dynamic programming element configured to receive actual operation metrics corresponding to the available actions. The approximate dynamic programming element can learn a state-action map and generate a dynamic treatment control policy using the one or more models.
    Type: Application
    Filed: February 10, 2014
    Publication date: June 5, 2014
    Applicant: The Trustees of Columbia University in the city of New York
    Inventors: Roger N. Anderson, Albert Boulanger, Leon L. Wu, Kevin Mclnerney, Timothy Teravainen, Bibhas Chakraborty
  • Patent number: 8725665
    Abstract: Techniques for evaluating the accuracy of a predicted effectiveness of an improvement to an infrastructure include collecting data, representative of at least one pre-defined metric, from the infrastructure during first and second time periods corresponding to before and after a change has been implemented, respectively. A machine learning system can receive compiled data representative of the first time period and generate corresponding machine learning data. A machine learning results evaluator can empirically analyze the generated machine learning data. An implementer can implement the change to the infrastructure based at least in part on the data from a machine learning data outputer. A system performance improvement evaluator can compare the compiled data representative of the first time period to that of the second time period to determine a difference, if any, and compare the difference, if any, to a prediction based on the generated machine learning data.
    Type: Grant
    Filed: August 20, 2012
    Date of Patent: May 13, 2014
    Assignee: The Trustees of Columbia University in the City of New York
    Inventors: Roger N. Anderson, Albert Boulanger, Leon Wu, Serena Lee
  • Patent number: 8725625
    Abstract: A capital asset planning system for selecting assets for improvement within an infrastructure that includes one or more data sources descriptive of the infrastructure, one or more databases, coupled to the one or more data sources, to compile the one or more data sources, one or more processors, each coupled to and having respective communication interfaces to receive data from the one or more databases. The processor includes a predictor to generate a first metric of estimated infrastructure effectiveness based, at least in part, on a current status of the infrastructure, a second metric of estimated infrastructure effectiveness based, at least in part, on a user-selected, proposed changed configuration of the infrastructure, and a net metric of infrastructure effectiveness based, at least in part, on said first metric and said second metric.
    Type: Grant
    Filed: October 8, 2012
    Date of Patent: May 13, 2014
    Assignees: The Trustees of Columbia University in the City of New York, Consolidated Edison Energy Company of New York
    Inventors: Roger N. Anderson, Maggie Chow, Albert Boulanger
  • Patent number: 8583405
    Abstract: A system and computer-implemented method of providing contingency analysis information for a utility service network that includes obtaining contingency analysis information from a plurality of external sources, integrally combining the contingency analysis information obtained from each of the plurality of external sources into a single application and prioritizing the contingency analysis information in a predetermined order, dynamically updating, the contingency analysis information obtained from each of the plurality of external sources and the prioritization of the contingency analysis information based on status information, and displaying the contingency analysis information to a user via a graphical user interface.
    Type: Grant
    Filed: May 11, 2010
    Date of Patent: November 12, 2013
    Inventors: Maggie Chow, Mark Mastrocinque, Robert J. Blick, Roger N. Anderson, Albert Boulanger, Philip Gross
  • Patent number: 8560476
    Abstract: A computer-aided lean management (CALM) controller system recommends actions and manages production in an oil and gas reservoir/field as its properties and conditions change with time. The reservoir/field is characterized and represented as an electronic-field (“e-field”). A plurality of system applications describe dynamic and static e-field properties and conditions. The application workflows are integrated and combined in a feedback loop between actions taken in the field and metrics that score the success or failure of those actions. A controller/optimizer operates on the combination of the application workflows to compute production strategies and actions. The controller/optimizer is configured to generate a best action sequence for production, which is economically “always-in-the-money.
    Type: Grant
    Filed: January 24, 2008
    Date of Patent: October 15, 2013
    Assignee: The Trustees of Columbia University in the City of New York
    Inventors: Roger N. Anderson, Albert Boulanger, Wei He, Ulisses Mello, Liqing Xu