Patents by Inventor Zihao ZHAO

Zihao ZHAO 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: 20250045594
    Abstract: An energy storage system and a thermal management method therefor are provided. The method includes: loading a multi-agent reinforcement learning model pre-trained and optimized through a simulation environment; receiving state observation data at a current time instant; inputting the state observation data into the multi-agent reinforcement learning model for reinforcement learning and reasoning to output multi-control action information; and generating a control action information instruction based on the multi-control action information, transmitting the control action information instruction to a cooling system in the energy storage system, and performing by the cooling system, thermal management on the energy storage system in response to the control action information instruction.
    Type: Application
    Filed: April 29, 2024
    Publication date: February 6, 2025
    Applicant: Sungrow Energy Storage Technology Co., Ltd.
    Inventors: Zihao Zhao, Jianjie Zhou, Tingting Hong, Xiaohui Cao, Fanglin Chen, Lulu Jiang
  • Patent number: 12014154
    Abstract: Methods and systems are presented for providing a computer platform that manages the impacts of government regulations on existing software processes of an online service provider. A regulation document is obtained from a government agency. The regulation document is processed, and legal obligations relevant to an online service provider are extracted from the regulation document. An ensemble machine learning model is used to recommend, for each of the legal obligations, software controls that can be implemented within one or more software processes of the online service provider to mitigate a risk of the legal obligations. The ensemble machine learning model may include an attribute-based model and a text-based model. An explainable visual interface is provided to present the recommended software controls and context that indicates to a user how the software controls are determined for the legal obligations.
    Type: Grant
    Filed: March 19, 2021
    Date of Patent: June 18, 2024
    Assignee: PAYPAL, INC.
    Inventors: Sneha Venkatachalam, Ravi Retineni, Hang Yu, Zhaoyang Wang, Yi Ren, Zihao Zhao, Huiting Li, Gaoyuan Wang, Li Cao
  • Publication number: 20240128770
    Abstract: A conversion power supply and an autonomous electric energy replenishment method for an energy storage system are provided. An output terminal of the power supply module is connected to a second side of a first DC-DC converter through an energy storage element. A first side of the first DC-DC converter is connected to battery clusters of the energy storage system through a DC interface of the conversion power supply, so that under control by a conversion power supply controller, in a case that a voltage of a battery cluster is lower than a preset threshold, the first DC-DC converter receives the electric energy on the second side, and transmit the electric energy to the first side of the first DC-DC converter, to realize a electric energy replenishment function for at least one of the battery clusters and prevent battery failure due to over-discharge.
    Type: Application
    Filed: July 12, 2023
    Publication date: April 18, 2024
    Applicant: Sungrow Power Supply Co., Ltd.
    Inventors: Jianjie Zhou, Xiaohui Cao, Fanglin Chen, Zihao Zhao
  • Publication number: 20240032493
    Abstract: Systems and methods are provided for automatically allocating test protocols to a plurality of test locations. Once such method includes a computing device executing a first stage machine learning prediction model (MLPM) based on protocol data for multiple test protocols for a test experiment to generate a first stage output. The first stage MLPM is trained based on historical allocation data for one or more prior test experiments. Multiple test sets are associated with the test protocols, and the first stage output includes, for multiple test locations, allocation prediction scores for the test protocols. Based on the first stage output, the computing device executes a second stage optimization model to generate a second stage output. The second stage output includes an allocation plan for the test protocols. The allocation plan identifies one or more of the test locations for each of the test protocols.
    Type: Application
    Filed: September 17, 2021
    Publication date: February 1, 2024
    Inventors: Xin SHEN, Aviral SHUKLA, Slobodan TRIFUNOVIC, Yiduo ZHAN, Zihao ZHAO
  • Publication number: 20230207548
    Abstract: The disclosure relates to a packaging structure for a power module, a packaging method and an electric vehicle. The packaging structure includes: a circuit board; at least one power chip, where each power chip is fastened on the circuit board, and each power chip is integrated with a sensor that is capable of detecting a working state of the power chip; and a signal chip, where the signal chip is fastened on the circuit board and separated from the power chip, a compiling program is preset in the signal chip, the signal chip is in a communication connection with each sensor, and the signal chip is configured to be capable of being in a communication connection with a predetermined device, so as to output working state data of each power chip to the predetermined device. By detecting the working state of each power chip, the power chip can be protected precisely in real time.
    Type: Application
    Filed: December 28, 2022
    Publication date: June 29, 2023
    Inventors: Haiyang CAO, Daohui LI, Fang QI, Zihao ZHAO, Pin ZENG
  • Publication number: 20230095351
    Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training a robotic control policy to perform a particular task. One of the methods includes performing a meta reinforcement learning phase including using training data collected for a plurality of different robotic control tasks and updating a robotic control policy according to the training data, wherein the robotic control policy is conditioned on an encoder network that is trained to predict which task is being performed from a context of a robotic operating environment; and performing an adaptation phase using a plurality of demonstrations for the particular task, including iteratively updating the encoder network after processing each demonstration of the plurality of demonstrations, thereby training the encoder network to learn environmental features of successful task runs.
    Type: Application
    Filed: September 15, 2022
    Publication date: March 30, 2023
    Inventors: Jianlan Luo, Stefan Schaal, Sergey Vladimir Levine, Zihao Zhao
  • Publication number: 20230091061
    Abstract: The present disclosure is applicable to the technical field of metering and distributing of an adhesive dispensing machine, and provides a machine learning-based flexible intelligent adhesive dispensing method.
    Type: Application
    Filed: April 29, 2022
    Publication date: March 23, 2023
    Inventors: Shen XU, Xiaohong YANG, Gongquan LIU, Zheyu LI, Ling WEI, Yong XIAO, Yong HUO, Feng WEI, Feng WANG, Songqiao ZHANG, Pengcheng DU, Fangfang JIANG, Fan JIANG, Long ZHANG, Baiteng GUO, Shuai LIU, Zihao ZHAO, Yirong MAO
  • Publication number: 20230023332
    Abstract: The present invention relates to the fields of medicinal chemistry and pharmacotherapeutics, and in particular to a 2-cyano-3,12-dioxoolean-1,9(11)-dien-17-phenylacrylamide derivative and a preparation method thereof; and the present invention further relates to use of the novel compound in the preparation of an anticancer medicament.
    Type: Application
    Filed: November 26, 2020
    Publication date: January 26, 2023
    Inventors: Guimin ZHANG, Hongbao LIANG, Li CHEN, Guifang ZHAO, Zihao ZHAO, Xiaoyan LU, Chenghong SUN
  • Publication number: 20220391676
    Abstract: A method of quantization evaluation, including, receiving a floating point data set, determining a floating point neural network model output utilizing the floating point data set, quantizing the floating point data set utilizing a quantization model yielding a quantized data set, determining a quantized neural network model output utilizing the quantized data set, determining whether an accuracy error between the floating point neural network model output and the quantized neural network model output exceeds an predetermined error tolerance, determining a floating point neural network tensor output utilizing the floating point data set if the predetermined error tolerance is exceeded, determining a quantized neural network tensor output utilizing the quantized data set if the predetermined error tolerance is exceeded, determining a per-tensor error based on the floating point neural network tensor output and the quantized neural network tensor output and updating the quantization model based on the per-tenso
    Type: Application
    Filed: June 4, 2021
    Publication date: December 8, 2022
    Inventors: Zihao Zhao, Chenghao Zhang, Yi Wang, Zexi Ye, Hui Wang, Zheng Qi, Qiang Zhang
  • Publication number: 20220284323
    Abstract: Methods and systems are presented for providing a computer platform that manages the impacts of government regulations on existing software processes of an online service provider. A regulation document is obtained from a government agency. The regulation document is processed, and legal obligations relevant to an online service provider are extracted from the regulation document. An ensemble machine learning model is used to recommend, for each of the legal obligations, software controls that can be implemented within one or more software processes of the online service provider to mitigate a risk of the legal obligations. The ensemble machine learning model may include an attribute-based model and a text-based model. An explainable visual interface is provided to present the recommended software controls and context that indicates to a user how the software controls are determined for the legal obligations.
    Type: Application
    Filed: March 19, 2021
    Publication date: September 8, 2022
    Inventors: Sneha Venkatachalam, Ravi Retineni, Hang Yu, Zhaoyang Wang, Yi Ren, Zihao Zhao, Huiting Li, Gaoyuan Wang, Li Cao
  • Publication number: 20220283782
    Abstract: Methods and systems are presented for providing a computer platform that manages the impacts of government regulations on existing software processes of an online service provider. A regulation document is obtained from a government agency. The regulation document is processed, and legal obligations relevant to an online service provider are extracted from the regulation document. An ensemble machine learning model is used to recommend, for each of the legal obligations, software controls that can be implemented within one or more software processes of the online service provider to mitigate a risk of the legal obligations. The ensemble machine learning model may include an attribute-based model and a text-based model. An explainable visual interface is provided to present the recommended software controls and context that indicates to a user how the software controls are determined for the legal obligations.
    Type: Application
    Filed: March 19, 2021
    Publication date: September 8, 2022
    Inventors: Sneha Venkatachalam, Ravi Retineni, Hang Yu, Zhaoyang Wang, Yi Ren, Zihao Zhao, Huiting Li, Gaoyuan Wang, Li Cao
  • Publication number: 20220283783
    Abstract: Methods and systems are presented for providing a computer platform that manages the impacts of government regulations on existing software processes of an online service provider. A regulation document is obtained from a government agency. The regulation document is processed, and legal obligations relevant to an online service provider are extracted from the regulation document. An ensemble machine learning model is used to recommend, for each of the legal obligations, software controls that can be implemented within one or more software processes of the online service provider to mitigate a risk of the legal obligations. The ensemble machine learning model may include an attribute-based model and a text-based model. An explainable visual interface is provided to present the recommended software controls and context that indicates to a user how the software controls are determined for the legal obligations.
    Type: Application
    Filed: March 19, 2021
    Publication date: September 8, 2022
    Inventors: Sneha Venkatachalam, Ravi Retineni, Hang Yu, Zhaoyang Wang, Yi Ren, Zihao Zhao, Huiting Li, Gaoyuan Wang, Li Cao
  • Patent number: 11429350
    Abstract: Methods and systems are presented for providing a computer platform that manages the impacts of government regulations on existing software processes of an online service provider. A regulation document is obtained from a government agency. The regulation document is processed, and legal obligations relevant to an online service provider are extracted from the regulation document. An ensemble machine learning model is used to recommend, for each of the legal obligations, software controls that can be implemented within one or more software processes of the online service provider to mitigate a risk of the legal obligations. The ensemble machine learning model may include an attribute-based model and a text-based model. An explainable visual interface is provided to present the recommended software controls and context that indicates to a user how the software controls are determined for the legal obligations.
    Type: Grant
    Filed: March 19, 2021
    Date of Patent: August 30, 2022
    Assignee: PayPal, Inc.
    Inventors: Sneha Venkatachalam, Ravi Retineni, Hang Yu, Zhaoyang Wang, Yi Ren, Zihao Zhao, Huiting Li, Gaoyuan Wang, Li Cao
  • Publication number: 20220172120
    Abstract: Systems and methods for use in identifying weights to be employed in a selection algorithm associated with plant advancement are disclosed. One example method includes identifying a start set of weights for a selection algorithm associated with a breeding program, and for each scale parameter value in a schedule, and for each of N iterations, modifying the start set of weights based on the scale parameter value, identifying a set of germplasm based on at least the modified set of weights, advancing the modified set of weights to a next iteration as the start set of weights when certain criteria are satisfied, and identifying the modified set of weights as an output when the iteration is equal to N.
    Type: Application
    Filed: December 1, 2021
    Publication date: June 2, 2022
    Inventors: Viveka GORLA, TingYu HO, Adam David SCOTT, Aviral SHUKLA, Yiduo ZHAN, Zihao ZHAO
  • Patent number: 10956700
    Abstract: The disclosure relates to a display device including: an organic light-emitting diode display panel, a fingerprint recognition layer located below the organic light-emitting diode display panel, and a light filtering layer located between the organic light-emitting diode display panel and the fingerprint recognition layer, where the light filtering layer is configured to filter out light rays with an incidence angle greater than a filter angle among light rays carrying fingerprint line information, and to transmit light rays with an incidence angle smaller than or equal to the filter angle, where the incidence angle is the angle between the light rays carrying fingerprint line information, and the direction perpendicular to the fingerprint recognition layer.
    Type: Grant
    Filed: July 23, 2019
    Date of Patent: March 23, 2021
    Assignees: Beijing BOE Display Tchnology Co., Ltd., BOE Technology Group Co., Ltd.
    Inventors: Ying Zhao, Shipei Li, Qingping Yin, Tao Li, Huili Wu, Chunming Cui, Zihao Zhao, Jie Jin, Weimeng Zhang
  • Publication number: 20200363684
    Abstract: A prism sheet, a backlight module, a display and a preparation method of the prism sheet are provided. The prism sheet includes a base layer and a prism layer located on a surface of a first side of the base layer, holes are provided inside the base layer, so that light received from a second side of the base layer reaches the prism layer through the holes, and the first side of the base layer and the second side of the base layer are opposite to each other.
    Type: Application
    Filed: March 12, 2019
    Publication date: November 19, 2020
    Inventor: Zihao ZHAO
  • Publication number: 20200210672
    Abstract: The disclosure relates to a display device including: an organic light-emitting diode display panel, a fingerprint recognition layer located below the organic light-emitting diode display panel, and a light filtering layer located between the organic light-emitting diode display panel and the fingerprint recognition layer, where the light filtering layer is configured to filter out light rays with an incidence angle greater than a filter angle among light rays carrying fingerprint line information, and to transmit light rays with an incidence angle smaller than or equal to the filter angle, where the incidence angle is the angle between the light rays carrying fingerprint line information, and the direction perpendicular to the fingerprint recognition layer.
    Type: Application
    Filed: July 23, 2019
    Publication date: July 2, 2020
    Inventors: Ying ZHAO, Shipei LI, Qingping YIN, Tao LI, Huili WU, Chunming CUI, Zihao ZHAO, Jie JIN, Weimeng ZHANG