Patents by Inventor Nathan O'Connor

Nathan O'Connor 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).

  • Patent number: 11348664
    Abstract: Techniques to suggest alternative chemical compounds that can be used to recreate or mimic a target flavor using artificial intelligence are disclosed. A neural network based model is trained on source chemical compounds and their corresponding flavors and odors. The neural network-based model learns compound embeddings of the source chemical compounds and a target chemical compound of a food item. From the compound embeddings, one or more chemical compounds that are closest to the target chemical compound may be determined by a distance metric. Each suggested chemical compound is an alternative that can be used to recreate functional features of the target chemical compound.
    Type: Grant
    Filed: June 17, 2021
    Date of Patent: May 31, 2022
    Assignee: NotCo Delaware, LLC
    Inventors: Kyohei Kaneko, Nathan O'Hara, Isadora Nun, Aadit Patel, Kavitakumari Solanki, Karim Pichara
  • Publication number: 20220136966
    Abstract: An artificial intelligence model receives a FTIR spectrum of a given ingredient to predict its protein secondary structure. The model includes three artificial modules, which generate three predicted values corresponding to structural categories (e.g., ?-helix, ?-sheet, and other) of the predicted secondary structure. Proteins may be compared for similarity based on predicted values corresponding to the structural categories of the predicted secondary structure.
    Type: Application
    Filed: February 19, 2021
    Publication date: May 5, 2022
    Inventors: Nathan O'Hara, Adil Yusuf, Julia Christin Berning, Francisca Villanueva, Rodrigo Contreras, Isadora Nun, Aadit Patel, Karim Pichara
  • Publication number: 20220099346
    Abstract: A sensor control system includes: a refrigerant leak sensor configured to, when powered, measure an amount of a refrigerant present in air outside of a heat exchanger of a refrigeration system, where the heat exchanger is located within a building that is at least one of heated and cooled by the refrigeration system; and a power control module configured to one of: continuously power the refrigerant leak sensor; and disconnect the refrigerant leak sensor from power when a blower that moves air past the heat exchanger is on.
    Type: Application
    Filed: September 29, 2020
    Publication date: March 31, 2022
    Applicant: Emerson Climate Technologies, Inc.
    Inventors: David ALFANO, Stuart K. MORGAN, Pham M. HUNG, Nathan O. BOYCE
  • Publication number: 20220054273
    Abstract: The present disclosure pertains to ankle prostheses. In an example embodiment, the ankle prosthesis comprises an adjustable and replaceable intermediate implant that is disposed between a tibial implant and a talar implant. The intermediate implant is adjustable relative to the tibial implant and can be interlocked therewith once adjusted. Methods of using, fitting, and adjusting the device are also described. Still other embodiments are described.
    Type: Application
    Filed: August 30, 2021
    Publication date: February 24, 2022
    Inventors: Shawn Thayer Huxel, John S. Crombie, Beat Hintermann, Andrew R. Fauth, Justin Hyer, Zachary C. Christensen, Trevor K. Lewis, Nathan O. Plowman, Neil Etherington, David Koch
  • Publication number: 20220041733
    Abstract: The disclosure provides a method for treating a subject afflicted with a tumor comprising administering to the subject a therapeutically effective amount of an anti-PD-1 antibody or antigen-binding portion thereof or an anti-PD-L1 antibody or antigen-binding portion thereof, wherein the subject is identified as having a high inflammatory gene signature score. In some embodiments, the high inflammatory gene signature score is determined by measuring the expression of a panel of inflammatory genes in a tumor sample obtained from the subject, wherein the inflammatory gene panel comprises CD274 (PD-L1), CD8A, LAG3, and STAT1.
    Type: Application
    Filed: March 27, 2020
    Publication date: February 10, 2022
    Applicant: Bristol-Myers Squibb Company
    Inventors: Ming LEI, Nathan O. SIEMERS, Dimple PANDYA, Han CHANG, Teresa K. SANCHEZ, Christopher T. HARBISON, Peter M. SZABO, Zachary S. BOYD, Alice M. WALSH
  • Publication number: 20220017548
    Abstract: The invention relates to compounds of formula I wherein R1, R2 and - - - - - are as defined herein, pharmaceutical compositions comprising the compounds and methods of treating COVID-19 in a patient by administering therapeutically effective amounts of the compounds and methods of inhibiting or preventing replication of SARS-CoV-2 with the compounds.
    Type: Application
    Filed: July 1, 2021
    Publication date: January 20, 2022
    Applicant: Pfizer Inc.
    Inventors: Robert Steven Kania, Padmavani Bezawada, Emma Louise Hawking, Rohit Jaini, Samir Kulkarni, Matthew Nathan O'Brien Laramy, Jonathan Richard Lillis, Suman Luthra, Dafydd Rhys Owen, Klimentina Dimitrova Pencheva, Martin Youngjin Pettersson, Anil Mahadeo Rane, Matthew Forrest Sammons, Bradley Paul Sullivan, Andrew John Thiel, Martyn David Ticehurst, Jamison Bryce Tuttle, Robert Louis Hoffman
  • Patent number: 11157828
    Abstract: Quantum neural nets, which utilize quantum effects to model complex data sets, represent a major focus of quantum machine learning and quantum computing in general. In this application, example methods of training a quantum Boltzmann machine are described. Also, examples for using quantum Boltzmann machines to enable a form of quantum state tomography that provides both a description and a generative model for the input quantum state are described. Classical Boltzmann machines are incapable of this. Finally, small non-stoquastic quantum Boltzmann machines are compared to traditional Boltzmann machines for generative tasks, and evidence presented that quantum models outperform their classical counterparts for classical data sets.
    Type: Grant
    Filed: June 16, 2017
    Date of Patent: October 26, 2021
    Assignee: Microsoft Technology Licensing, LLC
    Inventors: Nathan O. Wiebe, Maria Kieferova
  • Patent number: 11120359
    Abstract: Existing methods for dynamical simulation of physical systems use either a deterministic or random selection of terms in the Hamiltonian. In this application, example approaches are disclosed where the Hamiltonian terms are randomized and the precision of the randomly drawn approximation is adapted as the required precision in phase estimation increases. This reduces both the number of quantum gates needed and in some cases reduces the number of quantum bits used in the simulation.
    Type: Grant
    Filed: June 3, 2019
    Date of Patent: September 14, 2021
    Assignee: Microsoft Technology Licensing, LLC
    Inventors: Christopher Granade, Nathan O. Wiebe, Ian Kivlichan
  • Publication number: 20210276890
    Abstract: Disclosed herein are corrosion prevention devices comprising a sacrificial anode and a mass sensor. Also disclosed herein are corrosion prevention devices comprising a controller in communication with the mass sensor and sacrificial anode. The controller can be configured to receive mass data to detect when the mass of the sacrificial anode has fallen below a predetermined threshold. Upon determining that the mass has fallen below the predetermined threshold, the controller can designate that the sacrificial anode is depleted. In response, the controller can output instructions for performing one or more corrective actions to protect the desired structure from corrosion.
    Type: Application
    Filed: March 6, 2020
    Publication date: September 9, 2021
    Inventors: Nathan O. ANDREW, Colben T. FREEMAN
  • Patent number: 11103353
    Abstract: The present disclosure pertains to ankle prostheses. In an example embodiment, the ankle prosthesis comprises an adjustable and replaceable intermediate implant that is disposed between a tibial implant and a talar implant. The intermediate implant is adjustable relative to the tibial implant and can be interlocked therewith once adjusted. Methods of using, fitting, and adjusting the device are also described. Still other embodiments are described.
    Type: Grant
    Filed: September 18, 2017
    Date of Patent: August 31, 2021
    Assignee: DT MEDTECH, LLC
    Inventors: Shawn Thayer Huxel, John S. Crombie, Beat Hintermann, Andrew R. Fauth, Justin Hyer, Zachary C. Christensen, Trevor K. Lewis, Nathan O. Plowman, Neil Etherington, David Koch
  • Patent number: 11010450
    Abstract: The disclosed technology concerns example embodiments for estimating eigenvalues of quantum operations using a quantum computer. Such estimations are useful in performing Shor's algorithm for factoring, quantum simulation, quantum machine learning, and other various quantum computing applications. Existing approaches to phase estimation are sub-optimal, difficult to program, require prohibitive classical computing, and/or require too much classical or quantum memory to be run on existing devices. Embodiments of the disclosed approach address one or more (e.g., all) of these drawbacks. Certain examples work by using a random walk for the estimate of the eigenvalue that (e.g., only) keeps track of the current estimate and the measurement record that it observed to reach that point.
    Type: Grant
    Filed: June 29, 2018
    Date of Patent: May 18, 2021
    Assignee: Microsoft Technology Licensing, LLC
    Inventors: Christopher Granade, Nathan O. Wiebe
  • Patent number: 10990677
    Abstract: In this disclosure, a number of ways that quantum information can be used to help make quantum classifiers more secure or private are disclosed. In particular embodiments, a form of robust principal component analysis is disclosed that can tolerate noise intentionally introduced to a quantum training set. Under some circumstances, this algorithm can provide an exponential speedup relative to other methods. Also disclosed is an example quantum approach for bagging and boosting that can use quantum superposition over the classifiers or splits of the training set to aggregate over many more models than would be possible classically. Further, example forms of k-means clustering are disclosed that can be used to prevent even a powerful adversary from even learning whether a participant even contributed data to the clustering algorithm.
    Type: Grant
    Filed: June 15, 2017
    Date of Patent: April 27, 2021
    Assignee: Microsoft Technology Licensing, LLC
    Inventors: Nathan O. Wiebe, Ram Shankar Siva Kumar
  • Patent number: 10962473
    Abstract: An artificial intelligence model receives a FTIR spectrum of a given ingredient to predict its protein secondary structure. The model includes three artificial modules, which generate three predicted values corresponding to structural categories (e.g., ?-helix, ?-sheet, and other) of the predicted secondary structure. Proteins may be compared for similarity based on predicted values corresponding to the structural categories of the predicted secondary structure.
    Type: Grant
    Filed: November 5, 2020
    Date of Patent: March 30, 2021
    Assignee: NOTCO DELAWARE, LLC
    Inventors: Nathan O'Hara, Adil Yusuf, Julia Christin Berning, Francisca Villanueva, Rodrigo Contreras, Isadora Nun, Aadit Patel, Karim Pichara
  • Patent number: 10945859
    Abstract: Expandable fusion cages are disclosed which may be expandable in two substantially mutually perpendicular directions.
    Type: Grant
    Filed: January 29, 2019
    Date of Patent: March 16, 2021
    Assignee: AMPLIFY SURGICAL, INC.
    Inventors: Darin Ewer, Trevor K. Lewis, Justin Hyer, Nicholas Slater, Nathan O. Plowman
  • Publication number: 20210065037
    Abstract: Embodiments of a new approach for training a class of quantum neural networks called quantum Boltzmann machines are disclosed. in particular examples, methods for supervised training of a quantum Boltzmann machine are disclosed using an ensemble of quantum states that the Boltzmann machine is trained to replicate. Unlike existing approaches to Boltzmann training, example embodiments as disclosed herein allow for supervised training even in cases where only quantum examples are known (and not probabilities from quantum measurements of a set of states). Further, this approach does not require the use of approximations such as the Golden-Thompson inequality.
    Type: Application
    Filed: June 19, 2019
    Publication date: March 4, 2021
    Applicant: Microsoft Technology Licensing, LLC
    Inventors: Nathan O. Wiebe, Alexei Bocharov, Paul Smolensky, Matthias Troyer, Krysta Svore
  • Publication number: 20200359190
    Abstract: A method for detecting and distributing alert data based upon both receiving alert data encoded in a terrestrial television broadcast transmission and receiving an identification of a location of a device includes receiving, by a first device in a plurality of devices in a mesh network, a terrestrial broadcast signal including at least one datacast packet. A second device in the plurality of devices receives a satellite transmission identifying a location of the second device. The method includes confirming, by a notification engine executed by a third device in the plurality of devices in the mesh network, receipt of both the satellite transmission and alert data encoded in the terrestrial broadcast signal. The method includes activating, by the notification engine, at least one alert module in the mesh network, upon confirmation of the receipt of both the satellite transmission and the alert data encoded in the terrestrial broadcast signal.
    Type: Application
    Filed: May 1, 2020
    Publication date: November 12, 2020
    Inventors: Steven D. Hastings, Nathan O. Ford
  • Publication number: 20200349457
    Abstract: Methods for preparing a Gibbs state in a qubit register of a quantum computer include applying one or more quantum gates to one or more qubits of the qubit register to prepare a trial quantum state spanning the one or more qubits, the trial quantum state being defined as a function of parameters {right arrow over (?)} and being selected to provide an initial estimate of the Gibbs state. The methods further include evaluating the Gibbs free energy of the trial quantum state, adjusting the parameters {right arrow over (?)}, re-applying the one or more quantum gates to the one or more qubits to refine the trial quantum state according to the parameters {right arrow over (?)} as adjusted, and re-evaluating the Gibbs free energy of the trial quantum state.
    Type: Application
    Filed: April 30, 2019
    Publication date: November 5, 2020
    Applicant: Microsoft Technology Licensing, LLC
    Inventors: Guang Hao LOW, Nathan O. WIEBE, Anirban CH NARAYAN CHOWDHURY
  • Publication number: 20200293936
    Abstract: Existing methods for dynamical simulation of physical systems use either a deterministic or random selection of terms in the Hamiltonian. In this application, example approaches are disclosed where the Hamiltonian terms are randomized and the precision of the randomly drawn approximation is adapted as the required precision in phase estimation increases. This reduces both the number of quantum gates needed and in some cases reduces the number of quantum bits used in the simulation.
    Type: Application
    Filed: June 3, 2019
    Publication date: September 17, 2020
    Applicant: Microsoft Technology Licensing, LLC
    Inventors: Christopher Granade, Nathan O. Wiebe, Ian Kivlichan
  • Publication number: 20200279185
    Abstract: Methods to train a quantum Boltzmann machine (QBM) having one or more visible nodes and one or more hidden nodes. The methods comprise associating each visible and each hidden node of the QBM to a different corresponding qubit of a plurality of qubits of a quantum computer, wherein a state of each of the plurality of qubits contributes to a global energy of the QBM according to a set of weighting factors, and wherein the plurality of qubits include one or more output qubits corresponding to one or more visible nodes of the QBM. The methods further comprise providing a distribution of training data over the one or more output qubits, estimating a gradient of a quantum relative entropy between the output qubits and the distribution of training data, and training the set of weighting factors based on the estimated gradient using the quantum relative entropy as a cost function.
    Type: Application
    Filed: February 28, 2019
    Publication date: September 3, 2020
    Applicant: Microsoft Technology Licensing, LLC
    Inventors: Nathan O. WIEBE, Leonard Peter WOSSNIG
  • Patent number: 10517839
    Abstract: This application discloses methods for treating or preventing an ophthalmic retinal vascular permeability, angiogenic or fibroproliferative disease, disorder or condition that involve administering to a patient in need thereof a composition that can inhibit mast cell migration into the vitreous or the retina, mast cell proliferation in the vitreous or the retina, or mast cell secretion into the vitreous or the retina.
    Type: Grant
    Filed: June 9, 2009
    Date of Patent: December 31, 2019
    Assignee: Cornell University
    Inventors: Randi B. Silver, Nathan O'Connor