Patents by Inventor Caleb Grisell

Caleb Grisell 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: 20240394720
    Abstract: An online concierge system uses a machine-learned parking quality model to quantify the suitability of a particular parking location (e.g., a parking lot, or a street) for use when performing purchases at a retail location on behalf of customers. The parking quality model's output is determined according to input features related to parking at a candidate parking location, such as a current time, a current degree of demand for shoppers at the retail location, or a current average shopper wait time at the retail location before receiving an order. The online concierge system provides suggested alternate parking locations to a client device of the shopper, where they may be displayed, e.g., as part of an electronic map. Use of the suggested alternate parking locations helps to preserve parking availability in restricted areas such as retailer parking lots and to reduce traffic congestion in the area of the retailer.
    Type: Application
    Filed: May 26, 2023
    Publication date: November 28, 2024
    Inventors: Youdan Xu, Michael Chen, Marina Tanasyuk, Matthew Donghyun Kim, Ajay Pankaj Sampat, Caleb Grisell, Yuan Gao
  • Publication number: 20240289731
    Abstract: An online concierge system schedules pickers (shoppers) to fulfill orders from users. During periods of peak demand, the system increases compensation to shoppers to encourage more to participate, thereby reducing missed orders. The system determines an optimal multiplier to increase compensation based on predictive models of supply and demand and then applying an optimization algorithm to search different hyperparameters that affect how the models generate the multipliers. The system selects the optimal multipliers for different time periods and locations. The system may further present the multipliers being offered during future time periods and enable users to activate reminder alerts for select periods. The offers may be presented in a ranked list using a model trained to infer likelihoods of the user accepting participation and/or setting a reminder notification.
    Type: Application
    Filed: February 23, 2023
    Publication date: August 29, 2024
    Inventors: Youdan Xu, Matthew Donghyun Kim, Michael Chen, Marina Tanasyuk, Caleb Grisell, Adrian Mclean, Ajay Pankaj Sampat, Yuan Gao
  • Publication number: 20240202748
    Abstract: Techniques for predicting a wait time for a shopper based on a location the shopper's client device are presented. A system identifies a shopper's current location and uses a machine learning model to predict a wait time until the shopper will receive one or more orders. The machine learning model is trained to use input features including a number of orders received during a current time period for fulfillment near the current location, a number of other shoppers available for fulfilling orders during the current time period near the current location, historical information about a presentation of a plurality of orders to a plurality of shoppers near the current location, and historical information about the shopper and the other nearby available shoppers. The system then sends the predicted wait time to the client device for presentation to the shopper.
    Type: Application
    Filed: December 14, 2022
    Publication date: June 20, 2024
    Inventors: Radhika Anand, Ajay Pankaj Sampat, Caleb Grisell, Youdan Xu, Krishna Kumar Selvam, Bita Tadayon