Patents by Inventor Dian Li

Dian Li 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).

  • ANTIBODIES SPECIFICALLY BINDING TO CEACAM5
    Publication number: 20260028415
    Abstract: Provided herein are antibodies (e.g., sdAb such as VHH) specifically binding to CEACAM5, constructs and conjugates comprising the antibodies, and methods of making and uses thereof.
    Type: Application
    Filed: December 28, 2023
    Publication date: January 29, 2026
    Inventors: Chung Lim WONG, Ravi V. J. CHARI, Chieh-Ju LEE, Dian LI
  • Autonomous industrial process control system and method that provides autonomous retraining of forecast model
    Patent number: 11720068
    Abstract: The current disclosure is directed towards system and method for controlling industrial process. In one example, a method comprising deploying a forecast model for controlling an industrial process with training configurations that can be used as a single point of truth for guiding training and retraining versions of the forecast model using a model training algorithm without human input. The retraining and redeployment of the forecast model may be triggered when the performance of the forecast model degrades.
    Type: Grant
    Filed: January 6, 2020
    Date of Patent: August 8, 2023
    Assignee: OPRO.AI INC.
    Inventors: Hongbao Zhang, Roey Flor, Dian Li, Adam Schwab, Pengtao Xie, Eric Xing
  • AUTONOMOUS INDUSTRIAL PROCESS CONTROL SYSTEM AND METHOD THAT PROVIDES AUTONOMOUS RETRAINING OF FORECAST MODEL
    Publication number: 20210208545
    Abstract: The current disclosure is directed towards system and method for controlling industrial process. In one example, a method comprising deploying a forecast model for controlling an industrial process with training configurations that can be used as a single point of truth for guiding training and retraining versions of the forecast model using a model training algorithm without human input. The retraining and redeployment of the forecast model may be triggered when the performance of the forecast model degrades.
    Type: Application
    Filed: January 6, 2020
    Publication date: July 8, 2021
    Inventors: Hongbao Zhang, Roey Flor, Dian Li, Adam Schwab, Pengtao Xie, Eric Xing