Maria M Chang

20200193853, Jun 18, 2020

Feb 26, 2020

16/802491

- Armonk NY, US
Maria D. Chang - Irvington NY, US
Sharad Sundararajan - Yorktown Heights NY, US
Ravi Tejwani - Cambridge MA, US
Patrick D. Watson - Montrose NY, US

G09B 5/12
G09B 5/06
G09B 7/02

A method and system of providing education content to a student is provided. A topic to be taught to a student is received. A user model of the student is identified. An electronic content model for the topic is determined. One or more presentation templates are identified based on the electronic content model. A concept map is determined based on the one or more presentation templates. A presentation template is selected from the one or more presentation templates. A segment of an educational content of the topic is provided to a user device of the student, based on the selected presentation template.

20200126440, Apr 23, 2020

Oct 23, 2018

16/168391

- Armonk NY, US
Tejas Indulal Dhamecha - Bangalore, IN
Smitkumar Narotambhai Marvaniya - Bangalore, IN
Maria Chang - Irvington NY, US

G09B 7/04
G06F 17/27
G06F 17/28

One embodiment provides a method, including: receiving, in an environment for developing a conversational tutor, domain content corresponding to a domain of the conversational tutor, wherein the conversational tutor comprises a conversational agent designed to assist students in learning a domain; receiving, at the environment, tutoring content developed by a user, wherein the tutoring content comprises a tutoring script comprising questions to be presented to the student during a tutoring session with the conversational tutor to assist the student in learning the domain; evaluating, within the environment, the tutoring content against the domain content, wherein the evaluating comprises (i) identifying missing tutoring content, (ii) identifying the difficulty of the tutoring content, and (iii) identifying question dependencies; and providing, at the environment, at least one recommendation, identified from results of the evaluation, for adjusting the tutoring content.

20200065697, Feb 27, 2020

Aug 22, 2018

16/108324

- Armonk NY, US
Maria CHANG - Irvington NY, US
Jae-Wook AHN - Nanuet NY, US
Sharad Chandra SUNDARARAJAN - Bangalore, IN
Prasenjit DEY - Bangalore, IN

G06N 20/00

Techniques for assessing the proficiency of artificial intelligence agents and users in a given knowledge domain are described. A plurality of proficiency agents can be initialized with a plurality of proficiency scores, by performing a plurality of assessments between pairs of proficiency agents selected from the plurality of proficiency agents. A first client device associated with a first user is matched with a first proficiency agent of the plurality of proficiency agents, based on a first proficiency score associated with the first user and a second proficiency score of the plurality of proficiency scores corresponding to the first proficiency agent. Assessments results of an assessment performed between the first client device and the first proficiency agent are received, and a rating system update function is used to update the first proficiency score and the second proficiency score, based on the assessment results.

20200028843, Jan 23, 2020

Jul 17, 2018

16/037542

- Armonk NY, US
Tengfei Ma - White Plains NY, US
Maria Chang - Irvington NY, US
Jae-Wook Ahn - Nanuet NY, US
Ravi Tejwani - White Plains NY, US
Aldis Sipolins - New York City NY, US

H04L 29/06
G06F 3/01

A method for authenticating a user is presented. Responsive to a request for access to a computer resource, a computer system prompts the user making the request to access the computer resource to perform a new motion in an environment in which the user is monitored by a sensor system. Detected biometric data in the new motion performed by the user is identified by the computer system. A determination is made as to whether the user performing the new motion is an authenticated user based on comparing the detected biometric data with stored biometric data for a prior motion performed by the authenticated user. The computer system provides access to the computer resource when the user is identified as the authenticated user.

20190340541, Nov 7, 2019

May 3, 2018

15/969917

- Armonk NY, US
Maria Chang - Irvington NY, US
Tengfei Ma - White Plains NY, US
Aldis Sipolins - New York City NY, US

G06N 99/00
H04L 29/06
G06N 3/08

Techniques that facilitate layered stochastics anonymization of data are provided. In one example, a system includes a machine learning component and an evaluation component. The machine learning component performs a machine learning process for first data associated with one or more features to generate second data indicative of one or more example datasets within a degree of similarity to the first data. The first data and the second data comprise a corresponding data format. The evaluation component evaluates the second data for a particular feature from the one or more features and generates third data indicative of a confidence score for the second data.

20190222428, Jul 18, 2019

Mar 20, 2019

16/359476

- Armonk NY, US
Maria D. Chang - Irvington NY, US
Ravindranath Kokku - Yorktown Heights NY, US
Patrick Watson - Ossining NY, US

H04L 9/32
H04L 9/06
G06F 21/64
G06F 21/62

Techniques facilitating using a blockchain system that integrates the trustworthiness of the blockchain concept with open scientific research by generating a blockchain of the experiments formed, data collected, analyses performed, and results achieved are provided herein. In an example, the blockchain system can form a blockchain representing a research project, wherein the blockchain comprises a first block of research data and a second block of analysis data representing a log of an analysis performed on the research data. Summary blocks and correction blocks can also be added to the blockchain representing the post analysis of the research results. One or more of the subsequent blocks can be linked to the preceding blocks using information in block headers that can also serve to determine whether modifications to the blocks have been performed.

20190213256, Jul 11, 2019

Jan 11, 2018

15/868399

- Armonk NY, US
Maria D. CHANG - Irvington NY, US
Jae-Wook AHN - Nanuet NY, US
Sharad SUNDARARAJAN - Yorktown Heights NY, US
Tengfei MA - White Plains NY, US

G06F 17/27
G06F 17/30
G06N 3/04
G06N 3/08

Method and apparatus for generating natural language observations using sequence-to-sequence models are provided. The method includes receiving a first electronic document and dynamically generating, without requiring user intervention, a first natural language observation corresponding to a first portion of the first electronic document by processing the first portion of the first electronic document using a first sequence-to-sequence model. A second natural language observation is received for the first portion of the first electronic document, and the generated first natural language observation and the authoritative natural language observation are provided. The method further includes receiving an evaluation of the first natural language observation and the second natural language observation, and refining the first sequence-to-sequence model based on the evaluation of the first natural language observation and second natural language observation.

20180373974, Dec 27, 2018

Jun 27, 2017

15/634451

- Armonk NY, US
Maria D. CHANG - Irvington NY, US
Sharad SUNDARARAJAN - Yorktown Heights NY, US
Patrick D. WATSON - Ossining NY, US

G06N 3/00
G06N 99/00

Systems, methods, and computer program products to perform an operation comprising receiving text input via a chat interface of a tutor application, identifying, by at least one classifier applied to the text input, a concept in the text input, mapping the concept in the text input to at least one of a visual action and a first visual object, generating, based on a first machine learning (ML) model, a first program code statement corresponding to the at least one of the visual action and the first visual object, and executing the first program code statement to modify a visualization interface of the tutor application based on the text input received via the chat interface.