Patents by Inventor Deepak Chandra

Deepak Chandra 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: 20250095403
    Abstract: Methods, systems, and computer readable storage media for using image processing to develop a library of facial expressions. The system can receive digital video of at least one speaker, then execute image processing on the video to identify landmarks within facial features of the speaker. The system can also identify vectors based on the landmarks, then assign each vector to an expression, resulting in a plurality of speaker expressions. The system then scores the expressions based on similarity to one another, and creates subsets based on the similarity scores.
    Type: Application
    Filed: December 5, 2024
    Publication date: March 20, 2025
    Inventors: Deepak Chandra Sekar, Pranav Mehta
  • Patent number: 12254007
    Abstract: Systems and techniques are disclosed for generating entries for a searchable index based on rules generated by one or more machine-learned models. The index entries can include one or more tokens correlated with an outcome and an outcome probability. A subset of tokens can be identified based on the characteristics of an event. The index may be searched for outcomes and their respective probabilities that correspond to tokens that are similar to or match the subset of tokens based on the event.
    Type: Grant
    Filed: October 6, 2023
    Date of Patent: March 18, 2025
    Assignee: Google LLC
    Inventors: Jeremiah Harmsen, Tushar Deepak Chandra, Marcus Fontoura
  • Publication number: 20250072085
    Abstract: A power semiconductor device and a method of manufacturing a power semiconductor device is provided, including a shield gate trench (SGT) metal-oxide semiconductor field-effect transistor (MOSFET). The present disclosure provides for a MOSFET with a reduced charge between the gate conductive region and the drain or collector region, in order to improve the switching efficiency of the MOSFET.
    Type: Application
    Filed: August 20, 2024
    Publication date: February 27, 2025
    Applicant: NEXPERIA B.V.
    Inventors: Chih-Wei Hsu, Deepak Chandra Pandey, Adam Brown
  • Publication number: 20250072029
    Abstract: A method of manufacturing a semiconductor power device is provided. The method includes forming at least two trench regions within a semiconductor region, etching each trench region so that the mesa region extends above an upper surface of each trench region, and forming a plurality of spacers, where the spacers are located over each trench region and are adjacent to the mesa region.
    Type: Application
    Filed: August 23, 2024
    Publication date: February 27, 2025
    Applicant: NEXPERIA B.V.
    Inventors: Deepak Chandra Pandey, Steven Peake
  • Publication number: 20250055868
    Abstract: An authentication method for use in a device and comprises monitoring a program behavior stream comprising a plurality of program observables that comprises a program observable. The method records the program observable and matches the recorded first program observable to a program model selected from a plurality of program models stored within a program store. A user model is selected from a plurality of user models stored within a user store corresponding to the program model. A user behavior stream corresponding to the program observable is monitored and a user observable contained in the user behavior stream is recorded. The user observable is correlated to the user model and an authentication state associated with the device is determined based on the correlating.
    Type: Application
    Filed: August 30, 2024
    Publication date: February 13, 2025
    Inventors: Deepak Chandra DUTT, Anil Buntwal SOMAYAJI, Michael John Kendal BINGHAM
  • Patent number: 12219758
    Abstract: Some embodiments include an integrated assembly having a carrier-sink-structure, and having digit lines over the carrier-sink-structure. Transistor body regions are over the digit lines. Extensions extend from the carrier-sink-structure to the transistor body regions. The extensions are configured to drain excess carriers from the transistor body regions. Lower source/drain regions are between the transistor body regions and the digit lines, and are coupled with the digit lines. Upper source/drain regions are over the transistor body regions, and are coupled with storage elements. Gates are adjacent the transistor body regions. The transistor body regions, lower source/drain regions and upper source/drain regions are together comprised a plurality of transistors. The transistors and the storage elements are together comprised by a plurality of memory cells of a memory array. Some embodiments include methods of forming integrated assemblies.
    Type: Grant
    Filed: January 31, 2024
    Date of Patent: February 4, 2025
    Assignee: Micron Technology, Inc.
    Inventors: Kamal M. Karda, Haitao Liu, Durai Vishak Nirmal Ramaswamy, Yunfei Gao, Sanh D. Tang, Deepak Chandra Pandey
  • Publication number: 20240429056
    Abstract: There is provided a method of manufacturing a manufacturing intermediate for a semiconductor package, the method including: providing a die; at least partially encapsulating the die within a moulding compound; and thinning the die. There is further provided a manufacturing intermediate for a semiconductor package, including: a die having a first surface and a second surface; and a moulding encapsulating the die; in which the first surface of the die is exposed.
    Type: Application
    Filed: June 21, 2024
    Publication date: December 26, 2024
    Applicant: NEXPERIA B.V.
    Inventors: Ricardo Yandoc, Deepak Chandra Pandey
  • Publication number: 20240428411
    Abstract: Systems and methods are disclosed for predicting one or more medical conditions utilizing digital images and employing artificial intelligent algorithms. The system offers accurate predictions utilizing quantized pre-trained deep learning model. The pre-trained deep learning model is trained on data samples and later refined as the system processes more digital images or new medical conditions are incorporated. One pre-trained deep learning model is used to predict the probability of one or more medical conditions and identify locations in the digital image effected by the one or more medical conditions. Further, one pre-trained deep learning model utilizing additional data and plurality of digital images, forecasts rate of infection and spread of the medical condition over time.
    Type: Application
    Filed: September 10, 2024
    Publication date: December 26, 2024
    Applicant: Blaize, Inc.
    Inventors: Deepak Chandra Bijalwan, Dinakar C. Munagala
  • Publication number: 20240414531
    Abstract: A system for implicit authentication for a mobile device associated with a user, wherein the implicit authentication is behavioral, biometric and task-based and includes at least one authentication task selected so as to leverage the user's muscle memory. The mobile device comprises a touchscreen; a transaction authentication information unit; one or more sensors coupled to the transaction authentication information unit; and an anomaly detector coupled to the transaction authentication information unit. The sensors comprise one or more touchscreen sensors coupled to the touchscreen, an accelerometer, and a gyroscope, and are used to obtain and transmit one or more sets of data to the transaction authentication information unit. The sets of data are associated with one or more performances of the authentication task by the user. The anomaly detector generates an authentication model using the one or more data sets transmitted to the transaction authentication information unit.
    Type: Application
    Filed: June 11, 2024
    Publication date: December 12, 2024
    Inventors: Deepak Chandra DUTT, Anil Buntwal SOMAYAJI, Michael John Kendal BINGHAM
  • Patent number: 12166072
    Abstract: An example apparatus includes a first source/drain region and a second source/drain region formed in a substrate to form an active area of the apparatus. The first source/drain region and the second source/drain region are separated by a channel. The apparatus includes a gate opposing the channel. A sense line is coupled to the first source/drain region and a storage node is coupled to the second source/drain region. An isolation trench is adjacent to the active area. The trench includes a dielectric material with a conductive bias opposing the conductive bias of the channel in the active area.
    Type: Grant
    Filed: September 18, 2023
    Date of Patent: December 10, 2024
    Inventors: Kamal M. Karda, Haitao Liu, Si-Woo Lee, Fatma Arzum Simsek-Ege, Deepak Chandra Pandey, Chandra V. Mouli, John A. Smythe, III
  • Patent number: 12165433
    Abstract: Methods, systems, and computer readable storage media for using image processing to develop a library of facial expressions. The system can receive digital video of at least one speaker, then execute image processing on the video to identify landmarks within facial features of the speaker. The system can also identify vectors based on the landmarks, then assign each vector to an expression, resulting in a plurality of speaker expressions. The system then scores the expressions based on similarity to one another, and creates subsets based on the similarity scores.
    Type: Grant
    Filed: September 7, 2023
    Date of Patent: December 10, 2024
    Assignee: PROF JIM INC.
    Inventors: Deepak Chandra Sekar, Pranav Mehta
  • Publication number: 20240404262
    Abstract: The present disclosure relates to a system and method of performing quantization of a neural network having multiple layers. The method comprises receiving a floating-point dataset as input dataset and determining a first shift constant for first layer of the neural network based on the input dataset. The method also comprises performing quantization for the first layer using the determined shift constant of the first layer. The method further comprises determining a next shift constant for next layer of the neural network based on output of a layer previous to the next layer, and performing quantization for the next layer using the determined next shift constant. The method further comprises iterating the steps of determining shift constant and performing quantization for all layers of the neural network to generate fixed point dataset as output.
    Type: Application
    Filed: August 13, 2024
    Publication date: December 5, 2024
    Applicant: Blaize, Inc.
    Inventors: Deepak Chandra Bijalwan, Pratyusha Musunuru
  • Patent number: 12119269
    Abstract: An array of vertical transistors comprises spaced pillars individually comprising a channel region of individual vertical transistors. A horizontally-elongated conductor line directly electrically couples together individual of the channel regions of the pillars of a plurality of the vertical transistors. An upper source/drain region is above the individual channel regions of the pillars, a lower source/drain region is below the individual channel regions of the pillars, and a conductive gate line is operatively aside the individual channel regions of the pillars and that interconnects multiple of the vertical transistors. Methods are disclosed.
    Type: Grant
    Filed: May 25, 2022
    Date of Patent: October 15, 2024
    Assignee: Micron Technology, Inc.
    Inventors: Deepak Chandra Pandey, Haitao Liu, Kamal M. Karda
  • Patent number: 12112478
    Abstract: Systems and methods are disclosed for predicting one or more medical conditions utilizing digital images and employing artificial intelligent algorithms. The system offers accurate predictions utilizing quantized pre-trained deep learning model. The pre-trained deep learning model is trained on data samples and later refined as the system processes more digital images or new medical conditions are incorporated. One pre-trained deep learning model is used to predict the probability of one or more medical conditions and identify locations in the digital image effected by the one or more medical conditions. Further, one pre-trained deep learning model utilizing additional data and plurality of digital images, forecasts rate of infection and spread of the medical condition over time.
    Type: Grant
    Filed: December 19, 2023
    Date of Patent: October 8, 2024
    Assignee: Blaize, Inc.
    Inventors: Deepak Chandra Bijalwan, Dinakar C. Munagala
  • Publication number: 20240331445
    Abstract: Systems and methods of converting text into learning videos and assessments in different languages are described.
    Type: Application
    Filed: March 4, 2024
    Publication date: October 3, 2024
    Inventors: Deepak Chandra Sekar, Pranav Mehta
  • Patent number: 12100196
    Abstract: The present disclosure relates to a system and method of performing quantization of a neural network having multiple layers. The method comprises receiving a floating-point dataset as input dataset and determining a first shift constant for first layer of the neural network based on the input dataset. The method also comprises performing quantization for the first layer using the determined shift constant of the first layer. The method further comprises determining a next shift constant for next layer of the neural network based on output of a layer previous to the next layer, and performing quantization for the next layer using the determined next shift constant. The method further comprises iterating the steps of determining shift constant and performing quantization for all layers of the neural network to generate fixed point dataset as output.
    Type: Grant
    Filed: March 21, 2022
    Date of Patent: September 24, 2024
    Assignee: Blaize, Inc.
    Inventors: Deepak Chandra Bijalwan, Pratyusha Musunuru
  • Patent number: 12095788
    Abstract: An authentication method for use in a device and comprises monitoring a program behavior stream comprising a plurality of program observables that comprises a program observable. The method records the program observable and matches the recorded first program observable to a program model selected from a plurality of program models stored within a program store. A user model is selected from a plurality of user models stored within a user store corresponding to the program model. A user behavior stream corresponding to the program observable is monitored and a user observable contained in the user behavior stream is recorded. The user observable is correlated to the user model and an authentication state associated with the device is determined based on the correlating.
    Type: Grant
    Filed: May 21, 2021
    Date of Patent: September 17, 2024
    Assignee: Zighra Inc.
    Inventors: Deepak Chandra Dutt, Anil Buntwal Somayaji, Michael John Kendal Bingham
  • Publication number: 20240285130
    Abstract: A method for operating an automated food making apparatus having a motor, actuator arm, and an apparatus. The apparatus may be a paddle with flexible fins. The method rotates the paddle with a pin-shaft mechanism to dispense an ingredient placed in a canister, controls the motor automatically based on weight sensor readings, and locates a position of the actuator arm with position sensors. The same motor dispenses ingredients from a plurality of canisters. The method may have a plurality of paddle rotation and weight measurement steps until a target weight is reached. The plurality of paddle rotation steps may be unidirectional or bidirectional paddle rotation. The paddle may be rotated according to one or more paddle rotation algorithms, an error recovery algorithm, or different algorithms based on the amounts of ingredients remaining in the canister. The paddle may be rocked until the target weight is achieved.
    Type: Application
    Filed: February 16, 2024
    Publication date: August 29, 2024
    Inventors: Deepak Chandra Sekar, Kathirgugan Kathirasen, Brian Richardson, Sanath Bhat, Levi Lalla
  • Patent number: 12047773
    Abstract: A system for implicit authentication for a mobile device associated with a user, wherein the implicit authentication is behavioral, biometric and task-based and includes at least one authentication task selected so as to leverage the user's muscle memory. The mobile device comprises a touchscreen; a transaction authentication information unit; one or more sensors coupled to the transaction authentication information unit; and an anomaly detector coupled to the transaction authentication information unit. The sensors comprise one or more touchscreen sensors coupled to the touchscreen, an accelerometer, and a gyroscope, and are used to obtain and transmit one or more sets of data to the transaction authentication information unit. The sets of data are associated with one or more performances of the authentication task by the user. The anomaly detector generates an authentication model using the one or more data sets transmitted to the transaction authentication information unit.
    Type: Grant
    Filed: February 7, 2022
    Date of Patent: July 23, 2024
    Assignee: Zighra Inc.
    Inventors: Deepak Chandra Dutt, Anil Buntwal Somayaji, Michael John Kendal Bingham
  • Publication number: 20240232893
    Abstract: A system for authentication for a user device associated with a user, said system comprising: a processing system to generate a first user interface running on a screen of said user device, said first user interface comprising one or more components, wherein said one or more components comprises a first icon, which when activated, directs a user to a second user interface to select a secret pattern, a second icon, which when activated, generates a current randomly populated keyboard, further wherein said processing system provides a current Personal Identification Number (PIN) to said user by correlating said secret pattern with the current randomly populated keyboard, and a regular keyboard for said user to enter a PIN for authentication.
    Type: Application
    Filed: October 19, 2023
    Publication date: July 11, 2024
    Inventors: Deepak Chandra DUTT, Xun YIN, Zhaoyang WANG, Piotr Konrad TYSOWSKI, Mohammed Anwarul HASAN