Francisco Javier Leon

US Patent:

20220372146, Nov 24, 2022

Filed:

May 24, 2022

Appl. No.:

17/752650

Inventors:

- Red Bank NJ, US
Francisco Leon - Bethesda MD, US

Assignee:

Provention Bio, Inc. - Red Bank NJ

International Classification:

C07K 16/28
A61P 3/10

Abstract:

Provided herein are a method of treating type 1 diabetes (T1D) post SARS-CoV-2 infection. In some embodiments, such method can include administering to a subject in need thereof a 12-day course of teplizumab at a total dose of more than about 9000 μg/m.

US Patent:

20230004560, Jan 5, 2023

Filed:

Sep 9, 2022

Appl. No.:

17/930821

Inventors:

- McLean VA, US
Qingyi SUI - Falls Church VA, US
Mohammad SHAMI - Foster City CA, US
Fernando SAN MARTIN JORQUERA - San Francisco CA, US
Francisco PEREZ LEON - Richmond CA, US

Assignee:

Capital One Services, LLC - McLean VA

International Classification:

G06F 16/2455
G06F 16/242
G06F 16/28

Abstract:

Disclosed are systems and methods for monitoring user-defined metrics. A method may include: receiving, from a user device, a metric definition usable to generate queries to obtain data for a metric to be monitored; receiving, from the user device, a monitoring configuration indicative of a manner in which a metric monitoring process associated with the metric definition is to be repeatedly performed; storing the metric definition in a metric definition database; and repeatedly performing the metric monitoring process in accordance with the monitoring configuration. The metric monitoring process may include: retrieving the metric definition from the metric definition database; generating a database query based on the metric definition, the database query including one or more executable database statements defined by the metric definition; executing the database query to obtain query result data, the query result data being data for the metric; and storing the query result data.

US Patent:

20210334274, Oct 28, 2021

Filed:

Apr 28, 2020

Appl. No.:

16/860154

Inventors:

- McLean VA, US
Qingyi Sui - Falls Church VA, US
Mohammad Shami - Foster City CA, US
Fernando San Martin Jorquera - Los Altos CA, US
Francisco Perez Leon - Richmond CA, US

Assignee:

Capital One Services, LLC - McLean VA

International Classification:

G06F 16/2455
G06F 16/242
G06F 16/28

Abstract:

Disclosed are systems and methods for monitoring user-defined metrics. A method may include: receiving, from a user device, a metric definition usable to generate queries to obtain data for a metric to be monitored; receiving, from the user device, a monitoring configuration indicative of a manner in which a metric monitoring process associated with the metric definition is to be repeatedly performed; storing the metric definition in a metric definition database; and repeatedly performing the metric monitoring process in accordance with the monitoring configuration. The metric monitoring process may include: retrieving the metric definition from the metric definition database; generating a database query based on the metric definition, the database query including one or more executable database statements defined by the metric definition; executing the database query to obtain query result data, the query result data being data for the metric; and storing the query result data.

US Patent:

20200097981, Mar 26, 2020

Filed:

Jan 21, 2019

Appl. No.:

16/253065

Inventors:

- McLean VA, US
Volodymyr ORLOV - McLean VA, US
Yazdan SHIRVANY - McLean VA, US
Fernando SAN MARTIN JORQUERA - McLean VA, US
Francisco PEREZ LEON - McLean VA, US
Mohammad SHAMI - McLean VA, US

Assignee:

Capital One Services, LLC - McLean VA

International Classification:

G06Q 30/00
H04L 29/08
G06N 20/00
G06Q 30/02
H04M 3/51

Abstract:

Systems and methods for customizing business applications based upon user intent scores is described. A machine learning model trained to specifically predict when a user is likely to engage in a specific activity while interacting with the business application may be trained using data regarding prior interactions between a business application and a plurality of users. The machine learning model may thereafter provide a probability score for a particular user, the probability score indicating the likelihood that the user will engage in the specific activity for which the model has been trained to predict. The probability may be combined with a business value factor to produce a user intent score indicating the relative value of the user engaging in the specific activity. A business application comprising an app executing on a client device, a webpage, an automated menu at a call-in service center, or human operator interacting with the user at a call in the service center may be customized for the particular user based upon the user intent scores.