Patents Assigned to Carnegie Mellon
  • Patent number: 11768949
    Abstract: A system and method configures permission settings for applications (“apps”) running on a computing device of a user. A data center generates at least one model of collective privacy preferences. The computing device is in communication with the data center via a communications network. The computing device comprises a processor that execute at least a first app that requests access to at least one permission of the computing device and a personal privacy assistant app. The personal privacy assistant app receives the at least one model from the one or more servers of the data center; collects information about the user; identifies at least one recommended permission setting for the first app based on the at least one model and such that the recommended permission setting is user-specific; and configures the computing device to implement the received at least one user-specific recommended permission setting.
    Type: Grant
    Filed: February 2, 2021
    Date of Patent: September 26, 2023
    Assignee: Carnegie Mellon University
    Inventors: Norman Sadeh, Bin Liu, Anupam Das, Martin Degeling, Florian Schaub
  • Patent number: 11763798
    Abstract: Embodiments are provided to recognize features and activities from an audio signal. In one embodiment, a model is generated from sound effect data, which is augmented and projected into an audio domain to form a training dataset efficiently. Sound effect data is data that has been artificially created or from enhanced sounds or sound processes to provide a more accurate baseline of sound data than traditional training data. The sound effect data is augmented to create multiple variants to broaden the sound effect data. The augmented sound effects are projected into various audio domains, such as indoor, outdoor, urban, based on mixing background sounds consistent with these audio domains. The model is installed on any computing device, such as a laptop, smartphone, or other device. Features and activities from an audio signal are then recognized by the computing device based on the model without the need for in-situ training.
    Type: Grant
    Filed: July 15, 2021
    Date of Patent: September 19, 2023
    Assignee: CARNEGIE MELLON UNIVERSITY
    Inventors: Gierad Laput, Karan Ahuja, Mayank Goel, Christopher Harrison
  • Patent number: 11752892
    Abstract: A method for the efficient placement of electric vehicle chargers in a target area couples vehicle dynamics and battery dynamics modeling with environmental factors to accurately incorporate the impact that the environment has on the range of the battery into the placement of the chargers by simulating trips of fleets of electric vehicles. The vehicles can be of various types, for example, motorcycles, cars, trucks or aircraft, and will each have their battery state of charge monitored as they traverse a simulated trip through the target area.
    Type: Grant
    Filed: April 7, 2022
    Date of Patent: September 12, 2023
    Assignee: Carnegie Mellon University
    Inventors: Venkatasubramanian Viswanathan, Matthew Guttenberg, Shashank Sripad
  • Patent number: 11747135
    Abstract: An energy optimized imaging system that includes a light source that has the ability to illuminate specific pixels in a scene, and a sensor that has the ability to capture light with specific pixels of its sensor matrix, temporally synchronized such that the sensor captures light only when the light source is illuminating pixels in the scene.
    Type: Grant
    Filed: July 19, 2019
    Date of Patent: September 5, 2023
    Assignees: Carnegie Mellon University, The Governing Council of the University of Toronto
    Inventors: Srinivasa Narasimhan, Supreeth Achar, Matthew O'Toole, Kiriakos Neoklis Kutulakos
  • Patent number: 11748627
    Abstract: A system for applying a neural network to an input instance. The neural network includes an optimization layer for determining values of one or more output neurons from values of one or more input neurons by a joint optimization parametrized by one or more parameters. An input instance is obtained. The values of the one or more input neurons to the optimization layer are obtained and input vectors for the one or more input neurons are determined therefrom. Output vectors for the one or more output neurons are computed from the determined input vectors by jointly optimizing at least the output vectors with respect to the input vectors to solve a semidefinite program defined by the one or more parameters. The values of the one or more output neurons are determined from the respective computed output vectors.
    Type: Grant
    Filed: May 12, 2020
    Date of Patent: September 5, 2023
    Assignees: ROBERT BOSCH GMBH, CARNEGIE MELLON UNIVERSITY
    Inventors: Csaba Domokos, Jeremy Zieg Kolter, Po-Wei Wang, Priya L. Donti
  • Patent number: 11744927
    Abstract: A method of forming a microneedle array can include forming a sheet of material having a plurality of layers and micromilling the sheet of material to form a microneedle array. At least one of the plurality of layers can include a bioactive component, and the microneedle array can include a base portion and plurality of microneedles extending from the base portion.
    Type: Grant
    Filed: April 28, 2020
    Date of Patent: September 5, 2023
    Assignees: University of Pittsburgh—Of the Commonwealth System of Higher Education, Carnegie Mellon University
    Inventors: Louis D. Falo, Jr., Geza Erdos, O. Burak Ozdoganlar
  • Patent number: 11748853
    Abstract: Disclosed herein is a method for performing blind deconvolutions of blurred images. The method approximates the proximal operators for the data fidelity term and the prior term of a minimization function using trained neural networks and solves the minimization using iterations of the Douglas-Rachford algorithm.
    Type: Grant
    Filed: April 27, 2021
    Date of Patent: September 5, 2023
    Assignee: Carnegie Mellon University
    Inventors: Marios Savvides, Raied Aljadaany, Dipan Kumar Pal
  • Patent number: 11742162
    Abstract: A MEMS/NEMS actuator based on a phase change material is described in which the volumetric change observed when the phase change material changes from a crystalline phase to an amorphous phase is used to effectuate motion in the device. The phase change material may be changed from crystalline phase to amorphous phase by heating with a heater or by passing current directly through the phase change material, and thereafter quenched quickly by dissipating heat into a substrate. The phase change material may be changed from the amorphous phase to a crystalline phase by heating at a lower temperature. An application of the actuator is described to fabricate a phase change nano relay in which the volumetric expansion of the actuator is used to push a contact across an airgap to bring it into contact with a source/drain.
    Type: Grant
    Filed: December 18, 2019
    Date of Patent: August 29, 2023
    Assignee: Carnegie Mellon University
    Inventors: James Best, Gianluca Piazza
  • Patent number: 11730730
    Abstract: Provided herein are small molecule-inhibitors of site-specific O-glycosylation and the identification of such using cell-based fluorescent biosensors. Also provided herein are methods of treating kidney disease and cancer, such as breast cancer.
    Type: Grant
    Filed: May 26, 2021
    Date of Patent: August 22, 2023
    Assignee: Carnegie Mellon University
    Inventors: Adam D. Linstedt, Lina Song, Collin Bachert
  • Patent number: 11732172
    Abstract: A method for synthesizing a thermally conductive and stretchable elastomer composite comprises mixing liquid metal and soft material (e.g., elastomer) in a centrifugal or industrial shear mixer under conditions such that the liquid metal forms microscale liquid metal droplets that are dispersed in the soft elastomer. Liquid metal-embedded elastomers, or “LMEEs,” formed in this manner dramatically increase the fracture energy of soft materials up to 50 times over an unfilled polymer. This extreme toughening is achieved by means of (i) increasing energy dissipation, (ii) adaptive crack movement, and (iii) effective elimination of the crack tip. Such properties arise from the deformability and dynamic rearrangement of the LM inclusions during loading, providing a new mechanism to not only prevent crack initiation, but also resist the propagation of existing tears for ultra-tough, highly functional soft materials.
    Type: Grant
    Filed: January 4, 2019
    Date of Patent: August 22, 2023
    Assignee: CARNEGIE MELLON UNIVERSITY
    Inventors: Navid Kazem, Michael D. Bartlett, Carmel Majidi
  • Patent number: 11729904
    Abstract: An efficient fabrication technique, including an optional design step, is used to create highly customizable wearable electronics. The method of fabrication utilizes rapid laser machining and adhesion-controlled soft materials. The method produces well-aligned, multi-layered materials created from 2D and 3D elements that stretch and bend while seamlessly integrating with rigid components such as microchip integrated circuits (IC), discrete electrical components, and interconnects. The design step can be used to create a 3D device that conforms to different-shaped body parts. These techniques are applied using commercially available materials. These methods enable custom wearable electronics while offering versatility in design and functionality for a variety of bio-monitoring applications.
    Type: Grant
    Filed: May 4, 2020
    Date of Patent: August 15, 2023
    Assignee: CARNEGIE MELLON UNIVERSITY
    Inventors: Eric J. Markvicka, Michael D. Bartlett, Carmel Majidi, Lining Yao, Guanyun Wang, Yi-Chin Lee, Gierad Laput
  • Publication number: 20230252796
    Abstract: A method of compositional feature representation learning for video understanding is described. The method includes individually processing a sequence of video frames received as an input of a feature map network to generate a plurality of feature maps. The method also includes binding the plurality of feature maps to a fixed set of slot variables using an attention model according to a motion segmentation signal. The method further includes combining slot states corresponding to the fixed set of slot variables into a combined feature map. The method also includes decoding the combined feature map to form a reconstructed sequence of video frames, in which objects discovered in the reconstructed sequence of video frames are identified.
    Type: Application
    Filed: December 8, 2022
    Publication date: August 10, 2023
    Applicants: TOYOTA RESEARCH INSTITUTE, INC., TOYOTA JIDOSHA KABUSHIKI KAISHA, THE REGENTS OF THE UNIVERSITY OF CALIFORNIA, THE BOARD OF TRUSTEES OF THE UNIVERSITY OF ILLINOIS, CARNEGIE MELLON UNIVERSITY
    Inventors: Zhipeng BAO, Pavel TOKMAKOV, Adrien David GAIDON, Allan JABRI, Yuxiong WANG, Martial HEBERT
  • Publication number: 20230241995
    Abstract: A method for the efficient management of a fleet of electric vehicles in a target area couples vehicle dynamics and battery dynamics modeling with environmental factors to accurately incorporate the impact that the environment has on the range of the battery into the placement of the chargers by simulating trips of fleets of electric vehicles. The vehicles can be of various types, for example, motorcycles, cars, trucks or aircraft, and will each have their battery state of charge monitored as they traverse a simulated trip through the target area.
    Type: Application
    Filed: March 31, 2023
    Publication date: August 3, 2023
    Applicant: Carnegie Mellon University
    Inventors: Venkatasubramanian Viswanathan, Matthew Guttenberg, Shashank Sripad
  • Patent number: 11713340
    Abstract: Described herein are novel divalent nucleobases that each bind two nucleic acid strands, matched or mismatched when incorporated into a nucleic acid or nucleic acid analog backbone (a genetic recognition reagent, or genetic recognition reagent). In one embodiment, the genetic recognition reagent is a peptide nucleic acid (PNA) or gamma PNA (?PNA) oligomer. Uses of the divalent nucleobases and monomers and genetic recognition reagents containing the divalent nucleobases also are provided.
    Type: Grant
    Filed: December 28, 2021
    Date of Patent: August 1, 2023
    Assignee: Carnegie Mellon University
    Inventors: Danith H. Ly, Suresh Kumar Gopalsamy, Arunava Manna
  • Patent number: 11708601
    Abstract: A micromechanical sensor comprising a nucleic acid or nucleic acid analog nanostructure, such as a DNA origami or tiled structure, sensor spring and fluorophores arranged in FRET pairs in the sensor spring is provided, as well as methods of using the micromechanical sensor.
    Type: Grant
    Filed: September 4, 2020
    Date of Patent: July 25, 2023
    Assignee: Carnegie Mellon University
    Inventors: Rebecca Taylor, Charlotte Andreasen, Ying Liu, Yishun Daphne Zhou
  • Patent number: 11708447
    Abstract: A statistical, cationic-functionalized norbornene copolymer is formed by a process including performing a vinyl addition polymerization in the presence of a metal catalyst of a first norbornene monomer substituted with a first alkyl group and at least a second norbornene monomer substituted with a second alkyl group, to form an intermediate norbornene copolymer. The second alkyl group includes a substituent which undergoes a substitution reaction with a precursor of a cationic group. The process further includes adding the precursor for the cationic group to the intermediate norbornene copolymer to form the cationic functionalized norbornene copolymer. The cationic group has a volume of 0.25 cm3/mol or greater (for example, a phosphonium group or an imidazolium group).
    Type: Grant
    Filed: April 29, 2021
    Date of Patent: July 25, 2023
    Assignee: CARNEGIE MELLON UNIVERSITY
    Inventors: Kevin Noonan, Ryan Selhorst, Jamie Gaitor
  • Patent number: 11704568
    Abstract: Systems and techniques for facilitating hand activity sensing are presented. In one example, a system obtains, from a wrist-worn computational device, hand activity data associated with a sustained series of hand motor actions in performance of a human task. The system also employs a machine learning technique to determine classification data indicative of a classification for the human task.
    Type: Grant
    Filed: October 9, 2019
    Date of Patent: July 18, 2023
    Assignee: CARNEGIE MELLON UNIVERSITY
    Inventors: Gierad Laput, Christopher Harrison
  • Patent number: 11699076
    Abstract: A system and computer implemented method for learning rules from a data base including entities and relations between the entities, wherein an entity is either a constant or a numerical value, and a relation between a constant and a numerical value is a numerical relation and a relation between two constants is a non-numerical relation. The method includes: deriving aggregate values from said numerical and/or non-numerical relations; deriving non-numerical relations from said aggregate values; adding said derived non-numerical relations to the data base; constructing differentiable operators, wherein a differentiable operator refers to a non-numerical or a derived non-numerical relation of the data base, and extracting rules from said differentiable operators.
    Type: Grant
    Filed: August 14, 2020
    Date of Patent: July 11, 2023
    Assignees: ROBERT BOSCH GMBH, CARNEGIE MELLON UNIVERSITY
    Inventors: Csaba Domokos, Daria Stepanova, Jeremy Zieg Kolter, Po-Wei Wang
  • Patent number: 11694438
    Abstract: Some embodiments of the present inventive concept provide for improved telepresence and other virtual sessions dynamic scaling and/or assignment of computing resources. An XR telepresence platform can allow for immersive multi-user video conferencing from within a web browser or other medium. The platform can support spatial audio and/or user video. The platform can scale to hundreds or thousands of users concurrently in a single or multiple virtual environments. Disclosed herein are resource allocation techniques for dynamically allocating client connections across multiple servers.
    Type: Grant
    Filed: March 3, 2022
    Date of Patent: July 4, 2023
    Assignee: Carnegie Mellon University
    Inventors: Anthony Rowe, Michael Farb, Ivan Liang, Edward Lu, Nuno Pereira, Eric Riebling
  • Patent number: 11692070
    Abstract: This document describes a process of producing gel microparticles, which are consistent in size and morphology. Through the process of coacervation, large volumes of gel microparticle slurry can be produced by scaling up reactor vessel size. Particles can be repeatedly dehydrated and rehydrated in accordance to their environment, allowing for the storage of particles in a non-solvent such as ethanol. Gel slurries exhibit a Bingham plastic behavior in which the slurry behaves as a solid at shear stresses that are below a critical value. Upon reaching the critical shear stress, the slurry undergoes a rapid decrease in viscosity and behaves as a liquid. The rheological behavior of these slurries can be adjusted by changing the compaction processes such as centrifugation force to alter the yield-stress. The narrower distribution and reduced size of these particles allows for an increase in FRESH printing fidelity.
    Type: Grant
    Filed: April 5, 2018
    Date of Patent: July 4, 2023
    Assignee: Carnegie Mellon University
    Inventors: Andrew Hudson, Thomas Hinton, Adam Feinberg, Andrew Lee