Caroline Kim

US Patent:

20220378450, Dec 1, 2022

Filed:

Aug 11, 2022

Appl. No.:

17/886092

Inventors:

- Irvine CA, US
Thanh Van Nguyen - Westminster CA, US
Caroline Kim - Signal Hill CA, US

International Classification:

A61B 17/22
A61M 1/00

Abstract:

An extension conduit for use with a system for aspirating thrombus includes a passageway extending between a distal end and a proximal end of the extension conduit, and a combined hydraulic and electrical control carried on the extension conduit and configured to be activated by a user to activate an electric switch while opening a valve to allow flow through the passageway.

US Patent:

20220257268, Aug 18, 2022

Filed:

Feb 14, 2022

Appl. No.:

17/671462

Inventors:

- Irvine CA, US
THANH VAN NGUYEN - WESTMINSTER CA, US
CAROLINE KIM - Signal Hill CA, US

Assignee:

WALK VASCULAR, LLC - Irvine CA

International Classification:

A61B 17/22
A61M 1/00

Abstract:

An extension conduit for use with a system for aspirating thrombus includes a passageway extending between a distal end and a proximal end of the extension conduit, and a combined hydraulic and electrical control carried on the extension conduit and configured to be activated by a user to activate an electric switch while opening a valve to allow flow through the passageway.

US Patent:

20230030341, Feb 2, 2023

Filed:

Jul 22, 2021

Appl. No.:

17/383114

Inventors:

- San Jose CA, US
Tak Yeon Lee - DaeJeon, KR
Andrew Thomson - Moraga CA, US
Vasanthi Holtcamp - Fremont CA, US
Ryan Rossi - Santa Clara CA, US
Fan Du - Milpitas CA, US
Caroline Kim - San Francisco CA, US
Tong Yu - San Jose CA, US
Shunan Guo - San Jose CA, US
Nedim Lipka - Santa Clara CA, US
Shriram Venkatesh Shet Revankar - San Jose CA, US
Nikhil Belsare - Foster City CA, US

International Classification:

G06N 3/08
H04L 12/26
G06F 40/186
G06N 3/04

Abstract:

The present disclosure relates to systems, non-transitory computer-readable media, and methods that utilize a dynamic user interface and machine learning tools to generate data-driven digital content and multivariate testing recommendations for distributing digital content across computer networks. In particular, in one or more embodiments, the disclosed systems utilize machine learning models to generate digital recommendations at multiple development stages of digital communications that are targeted on particular performance metrics. For example, the disclosed systems utilize historical information and recipient profile data to generate recommendations for digital communication templates, fragment variants of content fragments, and content variants of digital content items. Ultimately, the disclosed systems generate multivariate testing recommendations incorporating selected fragment variants to intelligently narrow multivariate testing candidates and generate more meaningful and statistically significant multivariate testing results.

US Patent:

20230018792, Jan 19, 2023

Filed:

Aug 11, 2022

Appl. No.:

17/886151

Inventors:

- Irvine CA, US
Thanh Van Nguyen - Westminster CA, US
Caroline Kim - Signal Hill CA, US

International Classification:

A61B 17/22
A61M 1/00
A61M 39/22

Abstract:

An extension conduit for use with a system for aspirating thrombus includes a passageway extending between a distal end and a proximal end of the extension conduit, and a combined hydraulic and electrical control carried on the extension conduit and configured to be activated by a user to activate an electric switch while opening a valve to allow flow through the passageway.

US Patent:

20180082217, Mar 22, 2018

Filed:

Sep 29, 2017

Appl. No.:

15/721040

Inventors:

- San Diego CA, US
Caroline Kim - San Francisco CA, US
Paul Rahilly - San Diego CA, US

International Classification:

G06N 99/00
G05B 23/02
G05B 19/418

Abstract:

A plant asset failure prediction system and associated method. The method includes receiving user input identifying a first target set of equipment including a first plurality of units of equipment. A set of time series waveforms from sensors associated with the first plurality of units of equipment are received, the time series waveforms including sensor data values. A processor is configured to process the time series waveforms to generate a plurality of derived inputs wherein the derived inputs and the sensor data values collectively comprise sensor data. The method further includes determining whether a first machine learning agent may be configured to discriminate between first normal baseline data for the first target set of equipment and first failure signature information for the first target set of equipment. The first normal baseline data of the first target set of equipment may be derived from a first portion of the sensor data associated with operation of the first plurality of units of equipment in a first normal mode and the first failure signature information may be derived from a second portion of the sensor data associated with operation of the first plurality of units of equipment in a first failure mode. Monitored sensor signals produced by the one or more monitoring sensors are received. The first machine learning agent is then and activated, based upon the determining, to monitor data included within the monitored sensor signals.