Patents by Inventor Zhenpeng Zhou

Zhenpeng Zhou 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).

  • Personalized Labeling for User Memory Exploration for Assistant Systems
    Publication number: 20240054156
    Abstract: In one embodiment, a method includes receiving a multimodal input from a first client system associated with a first user via an assistant xbot, wherein the multimodal input comprises first images captured by cameras of the first client system and voice inputs by the first user, wherein the voice inputs comprise personalized labels corresponding to the first images, storing the first images and the personalized labels as a first digital memory of the first user, receiving a user request by the first user referencing one or more of the personalized labels from the first client system via the assistant xbot, generating a response for the first user based on the first digital memory and the referenced personalized labels, and sending instructions for presenting the response to the first user to the first client system via the assistant xbot.
    Type: Application
    Filed: October 27, 2021
    Publication date: February 15, 2024
    Inventors: Joshuah Vincent, Ruchir Srivastava, Leon Zhan, Jiayang Tong, Zhiguang Wang, Guangqiang Dong, Zhenpeng Zhou, Xin Ming Fan
  • Group classification based on machine learning analysis of mass spectrometry data from sweat
    Patent number: 11416704
    Abstract: Machine learning analysis of mass spectrometry spectra from human sweat samples is used to determine characteristics of interest such as age, ethnicity, gender drug use and disease state directly from the m/z data. This avoids the difficult problem of performing a full chemical analysis of human sweat samples to determine the characteristics of interest.
    Type: Grant
    Filed: December 15, 2017
    Date of Patent: August 16, 2022
    Assignee: The Board of Trustees of the Leland Stanford Junior University
    Inventors: Richard N. Zare, Zhenpeng Zhou
  • Group Classification based on Machine Learning Analysis of Mass Spectrometry Data from Sweat
    Publication number: 20180173998
    Abstract: Machine learning analysis of mass spectrometry spectra from human sweat samples is used to determine characteristics of interest such as age, ethnicity, gender drug use and disease state directly from the m/z data. This avoids the difficult problem of performing a full chemical analysis of human sweat samples to determine the characteristics of interest.
    Type: Application
    Filed: December 15, 2017
    Publication date: June 21, 2018
    Inventors: Richard N. Zare, Zhenpeng Zhou