Patents by Inventor Daniel Rothenberg

Daniel Rothenberg 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).

  • Forecasting method with machine learning
    Patent number: 11921257
    Abstract: The systems and methods described herein provide a mechanism for collecting information from a diverse suite of sensors and systems, calculating the current precipitation, atmospheric water vapor, or precipitable water and other atmospheric-based phenomena based upon these sensor readings, and predicting future precipitation and atmospheric-based phenomena.
    Type: Grant
    Filed: May 16, 2022
    Date of Patent: March 5, 2024
    Assignee: The Tomorrow Companies Inc.
    Inventor: Daniel Rothenberg
  • Methods of manufacturing amino acid compositions
    Patent number: 11679089
    Abstract: This disclosure provides methods of manufacturing large-scale blended preparations comprising one or more amino acids wherein the preparations have certain properties.
    Type: Grant
    Filed: June 19, 2019
    Date of Patent: June 20, 2023
    Assignee: AXCELLA HEALTH INC.
    Inventors: Thomas Hanlon, Ralph Yamamoto, Denise K. Kwok, Daniel Rothenberg, Andrew M. Wood
  • FORECASTING METHOD WITH MACHINE LEARNING
    Publication number: 20220291420
    Abstract: The systems and methods described herein provide a mechanism for collecting information from a diverse suite of sensors and systems, calculating the current precipitation, atmospheric water vapor, or precipitable water and other atmospheric-based phenomena based upon these sensor readings, and predicting future precipitation and atmospheric-based phenomena.
    Type: Application
    Filed: May 16, 2022
    Publication date: September 15, 2022
    Inventor: Daniel ROTHENBERG
  • Forecasting method with machine learning
    Patent number: 11402542
    Abstract: The systems and methods described herein provide a mechanism for collecting information from a diverse suite of sensors and systems, calculating the current precipitation, atmospheric water vapor, or precipitable water and other atmospheric-based phenomena based upon these sensor readings, and predicting future precipitation and atmospheric-based phenomena.
    Type: Grant
    Filed: October 30, 2019
    Date of Patent: August 2, 2022
    Assignee: The Tomorrow Companies Inc.
    Inventor: Daniel Rothenberg
  • REDUCED VOLUME FORMULATIONS INCLUDING AMINO ACID ENTITIES
    Publication number: 20210128466
    Abstract: This disclosure provides compositions and methods for improving the dispersion of a hydrophobic amino acid entity in an aqueous suspension. This disclosure further provides compositions and methods for improving the stability of N-acetylcysteine in the presence of acetyl acceptors, e.g., carnitine.
    Type: Application
    Filed: October 9, 2020
    Publication date: May 6, 2021
    Inventors: Jason Legassie, Thomas Hanlon, Ralph Yamamoto, Daniel Rothenberg, Weijia Niu, Benjamin Farina
  • FORECASTING METHOD WITH MACHINE LEARNING
    Publication number: 20200132884
    Abstract: The systems and methods described herein provide a mechanism for collecting information from a diverse suite of sensors and systems, calculating the current precipitation, atmospheric water vapor, or precipitable water and other atmospheric-based phenomena based upon these sensor readings, and predicting future precipitation and atmospheric-based phenomena.
    Type: Application
    Filed: October 30, 2019
    Publication date: April 30, 2020
    Inventor: Daniel Rothenberg
  • METHODS OF MANUFACTURING AMINO ACID COMPOSITIONS
    Publication number: 20190388374
    Abstract: This disclosure provides methods of manufacturing large-scale blended preparations comprising one or more amino acids wherein the preparations have certain properties.
    Type: Application
    Filed: June 19, 2019
    Publication date: December 26, 2019
    Inventors: Thomas Hanlon, Ralph Yamamoto, Denise K. Kwok, Daniel Rothenberg, Andrew M. Wood