Rui Lan Zhang

8081583, Dec 20, 2011

Jul 11, 2008

12/171913

Jae Hong Ruy - Daejeon, KR
Jong Suk Chae - Daejeon, KR
Cheol Sig Pyo - Daejeon, KR
Bong Soo Kim - Daejeon, KR
Eun Ju Lee - Daejeon, KR
Myung Jong Lee - Paramus NJ, US
Tae Rim Park - New York NY, US
Rui Zhang - New York NY, US

Electronics & Telecommunications Research Institute - Daejeon
Research Foundation of the City University of New York - New York NY

H04L 12/26

370256

Provided is a method of supporting node portability in a sensor network, wherein data transmission to a portable node can be guaranteed since even when the portable node is assigned with a different address by being associated with another network, the newly assigned address is transmitted to a parent node or a sink node that was previously associated with the portable node.

20220414684, Dec 29, 2022

Jun 23, 2021

17/356084

- McLean VA, US
Rui ZHANG - New York NY, US
Erik MUELLER - Chevy Chase MD, US
Victor Alvarez MIRANDA - McLean VA, US

Capital One Services, LLC - McLean VA

G06Q 30/02
G06F 17/18
G06K 9/62
G06N 3/08

Provided herein are systems and methods for using multi-modal regression to predict customer intent to contact a merchant. Multi-modal data including numerical data and unstructured data are extracted from customer interactions with the merchant. Features of the numerical data and the unstructured data are separately extracted and classified using techniques specific to the data types. The features for each type are then separately used to predict probabilities of customer intent. A neural network is used to combine the predictions into a single set of estimates of customer intent. This set of estimates of customer intents is used to estimate a probability that the customer will contact the merchant. The customer is then contacted based on the estimate.

20220345425, Oct 27, 2022

Jul 6, 2022

17/811063

- McLean VA, US
Erik MUELLER - Chevy Chase MD, US
Rui ZHANG - New York NY, US

Capital One Services, LLC - McLean VA

H04L 51/02
G06F 17/18
G06N 3/04
G06N 20/20

Methods and systems are described for generating dynamic interface options using machine learning models. The dynamic interface options may be generated in real time and reflect the likely goals and/or intents of a user. The machine learning model may provide these features by interpreting multi-modal feature inputs. For example, the machine learning model may include a first machine learning model, wherein the first machine learning model comprises a convolutional neural network, and a second machine learning model, wherein the second machine learning model performs a Weight of Evidence (WOE) analysis.

20220263778, Aug 18, 2022

May 6, 2022

17/738224

- McLean VA, US
Victor ALVAREZ MIRANDA - McLean VA, US
Pamela KATALI - Gaithersburg MD, US
Arturo HERNANDEZ ZELEDON - Arlington VA, US
Rui ZHANG - New York NY, US

Capital One Services, LLC - McLean VA

H04L 51/02
G06K 9/62
G10L 15/16
G06N 20/20

Methods and systems are described for generating dynamic conversational responses using two-tier machine learning models. The dynamic conversational responses may be generated in real time and reflect the likely goals and/or intents of a user. The two-tier machine learning model may include a first tier that determines an intent cluster based on a feature input, and a second tier that determines a specific intent from the cluster.

20230008022, Jan 12, 2023

Nov 25, 2019

17/295497

Dane CLAUSEN - Kenilworth NJ, US
Ping CHEN - Kenilworth NJ, US
Xavier FRADERA - Boston MA, US
Liangqin GUO - Kenilworth NJ, US
Yongxin HAN - Boston MA, US
Shuwen HE - Fanwood NJ, US
Xianhai HUANG - Warren NJ, US
Joseph KOZLOWSKI - Princeton NJ, US
Guoqing LI - Kenilworth NJ, US
Theodore A. MARTINOT - Southborough MA, US
Alexander PASTERNAK - Boston MA, US
Andreas VERRAS - New York NY, US
Li XIAO - Kenilworth NJ, US
Wensheng YU - Kenilworth NJ, US
Rui ZHANG - Kenilworth NJ, US
- Rahway NJ, US

Merck Sharp & Dohme Corp. - Rahway NJ

C07D 231/56
C07D 491/052
C07D 231/54
A61K 31/496
C07D 401/12
C07D 401/14
C07D 413/12
A61K 31/5377
C07D 498/10
C07D 491/107
C07D 498/08
C07D 471/10
C07D 403/12
C07D 405/12
C07D 498/04
C07D 487/04
C07D 487/10
A61K 31/541
C07D 413/14

Disclosed herein are compounds of formula (I) which are inhibitors of an IDO enzyme: (I). Also disclosed herein are uses of the compounds in the potential treatment or prevention of an IDO-associated disease or disorder. Also disclosed herein are compositions comprising these compounds. Further disclosed herein are uses of the compositions in the potential treatment or prevention of an IDO-associated disease or disorder.

20230006908, Jan 5, 2023

Jun 30, 2021

17/364344

- McLean VA, US
Jimmy SAMBUO - McLean VA, US
Rui ZHANG - New York NY, US

Capital One Services, LLC - McLean VA

H04L 12/26
H04L 29/06

Provided herein are systems and methods for sanitizing logged data packets in a distributed system prior to storing them in a remote or third-party data server. Interactions with an application are monitored and values in a data packet are extracted from the interaction. The values are classified based on a classification configuration and respective labels of the values. The values are then sanitized based on the classification to prevent exposure of secure or private data. The sanitized data packets are then logged into the remote data server. The logged data can be used to help resolve events occurring in the application. The classification configuration can be iteratively updated and the interactions repeated to capture data that was previously sanitized to aid in resolution of events. The logged data can also be used in research or analysis, such as for identifying potential improvements to the application.

20210395240, Dec 23, 2021

Oct 28, 2019

17/287256

Dane CLAUSEN - Kenilworth NJ, US
- Rahway NJ, US
Liangqin Guo - Monroe Township NJ, US
Yongxin Han - Needham MA, US
Shuwen He - Fanwood NJ, US
Joseph Kozlowski - Princeton NJ, US
Guoqing Li - Belle Mead NJ, US
Theodore A. Martinot - Southborough MA, US
Alexander Pasternak - Jamaica Plain MA, US
David Sloman - Newton MA, US
Li Xiao - Cranbury NJ, US
Wensheng Yu - Edison NJ, US
Rui Zhang - Plainsboro NJ, US

Merck Sharp & Dohme Corp. - Rahway NJ

C07D 413/14
C07D 401/14

Disclosed herein are compounds of formula (I) which are inhibitors of an IDO enzyme: (I). Also disclosed herein are uses of the compounds in the potential treatment or prevention of an IDO-associated disease or disorder. Also disclosed herein are compositions comprising these compounds. Further disclosed herein are uses of the compositions in the potential treatment or prevention of an IDO-associated disease or disorder.

20210125612, Apr 29, 2021

Jul 28, 2020

16/940704

- McLean VA, US
Liwei Dai - Oakton VA, US
Erik T. Mueller - Chevy Chase MD, US
Rui Zhang - New York NY, US

G10L 15/22
G06N 20/00
G06Q 30/00
H04M 3/527
H04M 3/493
G10L 15/30
G10L 15/18

Systems and methods are provided herein for autonomously determining and resolving a customer's perceived discrepancy during a customer service interaction. The method can include receiving an incoming communication from a customer; extracting a perceived state and an expected state (possibly of a product or service) based on the incoming communication; determining a perceived discrepancy between the perceived and expected states of the customer; retrieving customer information; extracting a current state of the customer from the retrieved customer information, verifying, by a rule-based platform, the discrepancy; generating a response based on the discrepancy after comparing the perceived stated with the current state, where the response may include a confirmation or a correction related to the discrepancy and a personalized explanation describing the current state of the customer; and outputting, for presentation to the customer, the response.