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Chao Li

from Duluth, GA
Age ~65
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Related to:
Zhen K Lim, 75Qi LiGuanghui Li, 72Jixin Li, 56Jin Li Est, 68
Connected to:
Ai Q Li, 64Ai H Li, 81Aida Li, 67Aijun Li, 65Aiwen Q Li, 56Aiyan Li, 61Alan Li, 80Alice Li, 46Alida Li, 59Alisha Li, 31

Chao Li Phones & Addresses

  • 2455 Bretdale Rd, Duluth, GA 30096
  • Fremont, CA
  • Tallahassee, FL
  • Decatur, GA
  • Atlanta, GA

Education

School / High School: New York University, School of Law

Ranks

Licence: New York - Currently registered Date: 2009

Professional Records

License Records

Chao Li

Address:
4096 Forsythe Park Cir, Tallahassee, FL 32309
License #:
1100015144
Category:
Engineers
Issued Date:
Jan 29, 2011
Effective Date:
Jan 29, 2011
Type:
Engineering Intern

Chao Li

Address:
4096 Forsythe Park Cir, Tallahassee, FL 32309
License #:
73106 - Active
Category:
Engineers
Issued Date:
Jun 4, 2011
Effective Date:
Jun 4, 2011
Expiration Date:
Feb 28, 2019
Type:
Professional Engineer

Lawyers & Attorneys

Chao Li Photo 1

Chao Li - Lawyer

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Address:
(891) 018-5396 (Office)
Licenses:
New York - Currently registered 2009
Education:
New York University, School of Law
Chao Li Photo 2

Chao Li - Lawyer

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ISLN:
924296214
Admitted:
2009

Medicine Doctors

Chao Li Photo 3

Chao Li

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Resumes

Resumes

Chao Li Photo 4

Chao Li San Jose, CA

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Work:
AFFILIATION

Oct 2012 to 2000
Member, Accounting Association, UCSB
ALLEN ASSOCIATES
Santa Barbara, CA
Jul 2013 to Aug 2013
Temporary Accounting Assistant
CIB SECURITY
Sunnyvale, CA
Jun 2011 to Sep 2011
Technician
American Marketing Association

Sep 2009 to May 2010
Member
Education:
University of California-Santa Barbara
Santa Barbara, CA
Mar 2013
Bachelor of Art in Economic and Accounting
Ohlone College
Fremont, CA
Sep 2010 to May 2011
Business Administration
Central Michigan University
Mount Pleasant, MI
Jan 2007 to May 2010
Bachelor of Science in Business Administration
Chao Li Photo 5

Chao Li Santa Barbara, CA

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Work:
AFFILIATION

Oct 2012 to 2000
Member, Accounting Association, UCSB
CIB SECURITY
Sunnyvale, CA
Jun 2011 to Sep 2011
Technician
American Marketing Association

Sep 2009 to May 2010
Member
Real Food on Campus
Mount Pleasant, MI
Jun 2007 to Sep 2007
Server
Education:
University of California-Santa Barbara
Santa Barbara, CA
Mar 2013
Bachelor of Art in Economic and Accounting
Ohlone College
Fremont, CA
Sep 2010 to May 2011
Business Administration
Central Michigan University
Mount Pleasant, MI
Jan 2007 to May 2010
Bachelor of Science in Business Administration
Skills:
MS Word, Excel, Powerpoint, Chinese&English

Business Records

Name / Title
Company / Classification
Phones & Addresses
Chao Li
Secretary
CHAO LI, INC
3640 Shallowford Rd SUITE 44, Atlanta, GA
3193 Darlington Oak Dr, Atlanta, GA
Chao B. Li
MEBOOKS, LLC

Publications

Isbn (Books And Publications)

Location-based Services and Geo-information Engineering

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Author

Chao Li

ISBN #

0470857366

Location-based Services and Geo-information Engineering

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Author

Chao Li

ISBN #

0470857374

Us Patents

Anomaly Detection For An E-Commerce Pricing System

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US Patent:
20220237670, Jul 28, 2022
Filed:
Apr 15, 2022
Appl. No.:
17/721594
Inventors:
- Bentonville AR, US
Elham SHAABANI - Redwood City CA, US
Chao LI - San Carlos CA, US
Matyas A. SUSTIK - San Francisco CA, US
International Classification:
G06Q 30/02
G06K 9/62
G06Q 20/20
G06N 20/00
G06Q 10/06
Abstract:
This application relates to apparatus and methods for identifying anomalies within data, such as pricing data. In some examples, a computing device receives data updates and selects a machine learning model to apply to the data update. The computing device may train the machine learning model with features generated based on historical purchase order data. An anomaly score is generated based on application of the machine learning model. Based on the anomaly score, the data update is either allowed, or denied. In some examples, the computing device re-trains the machine learning model with detected anomalies. In some embodiments, the computing device prioritizes detected anomalies for further investigation. In some embodiments, the computing device identifies the cause of the anomalies by identifying at least one feature that is causing the anomaly.

Multiple Spacer Patterning Schemes

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US Patent:
20230093450, Mar 23, 2023
Filed:
Nov 30, 2022
Appl. No.:
18/072457
Inventors:
- Santa Clara CA, US
Rui CHENG - Santa Clara CA, US
Karthik JANAKIRAMAN - San Jose CA, US
Zubin HUANG - Santa Clara CA, US
Diwakar KEDLAYA - Santa Clara CA, US
Meenakshi GUPTA - San Jose CA, US
Srinivas GUGGILLA - San Jose CA, US
Yung-chen LIN - Gardena CA, US
Hidetaka OSHIO - Tokyo, JP
Chao LI - Santa Clara CA, US
Gene LEE - San Jose CA, US
International Classification:
H01L 21/033
H01L 21/311
H01L 21/3213
Abstract:
The present disclosure provides forming nanostructures utilizing multiple patterning process with good profile control and feature transfer integrity. In one embodiment, a method for forming features on a substrate includes forming a first mandrel layer on a material layer disposed on a substrate. A first spacer layer is conformally formed on sidewalls of the first mandrel layer, wherein the first spacer layer comprises a doped silicon material. The first mandrel layer is selectively removed while keeping the first spacer layer. A second spacer layer is conformally formed on sidewalls of the first spacer layer and selectively removing the first spacer layer while keeping the second spacer layer.

Methods And Apparatus For Anomaly Detections

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US Patent:
20200380570, Dec 3, 2020
Filed:
May 30, 2019
Appl. No.:
16/427238
Inventors:
- Bentonville AR, US
Elham SHAABANI - Redwood City CA, US
Chao LI - San Carlos CA, US
Matyas A. SUSTIK - San Francisco CA, US
International Classification:
G06Q 30/02
G06K 9/62
G06Q 10/06
G06N 20/00
G06Q 20/20
Abstract:
This application relates to apparatus and methods for identifying anomalies within data, such as pricing data. In some examples, a computing device receives data updates and selects a machine learning model to apply to the data update. The computing device may train the machine learning model with features generated based on historical purchase order data. An anomaly score is generated based on application of the machine learning model. Based on the anomaly score, the data update is either allowed, or denied. In some examples, the computing device re-trains the machine learning model with detected anomalies. In some embodiments, the computing device prioritizes detected anomalies for further investigation. In some embodiments, the computing device identifies the cause of the anomalies by identifying at least one feature that is causing the anomaly.

Methods And Apparatus For Anomaly Detections

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US Patent:
20200380571, Dec 3, 2020
Filed:
May 30, 2019
Appl. No.:
16/427241
Inventors:
- Bentonville AR, US
Elham SHAABANI - Redwood City CA, US
Chao LI - San Carlos CA, US
Matyas A. SUSTIK - San Francisco CA, US
International Classification:
G06Q 30/02
G06K 9/00
G06F 17/11
G06Q 10/06
G06N 20/00
G06Q 20/20
Abstract:
This application relates to apparatus and methods for identifying anomalies within data, such as pricing data. In some examples, a computing device receives data updates and selects a machine learning model to apply to the data update. The computing device may train the machine learning model with features generated based on historical purchase order data. An anomaly score is generated based on application of the machine learning model. Based on the anomaly score, the data update is either allowed, or denied. In some examples, the computing device re-trains the machine learning model with detected anomalies. In some embodiments, the computing device prioritizes detected anomalies for further investigation. In some embodiments, the computing device identifies the cause of the anomalies by identifying at least one feature that is causing the anomaly.

Multiple Spacer Patterning Schemes

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US Patent:
20200335338, Oct 22, 2020
Filed:
Mar 17, 2020
Appl. No.:
16/821759
Inventors:
- Santa Clara CA, US
Rui CHENG - Santa Clara CA, US
Karthik JANAKIRAMAN - San Jose CA, US
Zubin HUANG - Santa Clara CA, US
Meenakshi GUPTA - San Jose CA, US
Srinivas GUGGILLA - San Jose CA, US
Yung-chen LIN - Gardena CA, US
Hidetaka OSHIO - Tokyo, JP
Chao LI - Santa Clara CA, US
Gene LEE - San Jose CA, US
International Classification:
H01L 21/033
Abstract:
The present disclosure provides forming nanostructures utilizing multiple patterning process with good profile control and feature transfer integrity. In one embodiment, a method for forming features on a substrate includes forming a mandrel layer on a substrate, conformally forming a spacer layer on the mandrel layer, wherein the spacer layer is a doped silicon material, and patterning the spacer layer. In another embodiment, a method for forming features on a substrate includes conformally forming a spacer layer on a mandrel layer on a substrate, wherein the spacer layer is a doped silicon material, selectively removing a portion of the spacer layer using a first gas mixture, and selectively removing the mandrel layer using a second gas mixture different from the first gas mixture.

Multiple Spacer Patterning Schemes

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US Patent:
20200335339, Oct 22, 2020
Filed:
May 5, 2020
Appl. No.:
16/867095
Inventors:
- Santa Clara CA, US
Rui CHENG - Santa Clara CA, US
Karthik JANAKIRAMAN - San Jose CA, US
Zubin HUANG - Santa Clara CA, US
Diwakar KEDLAYA - Santa Clara CA, US
Meenakshi GUPTA - San Jose CA, US
Srinivas GUGGILLA - San Jose CA, US
Yung-chen LIN - Gardena CA, US
Hidetaka OSHIO - Tokyo, JP
Chao LI - Santa Clara CA, US
Gene LEE - San Jose CA, US
International Classification:
H01L 21/033
Abstract:
The present disclosure provides forming nanostructures utilizing multiple patterning process with good profile control and feature transfer integrity. In one embodiment, a method for forming features on a substrate includes forming a first mandrel layer on a material layer disposed on a substrate. A first spacer layer is conformally formed on sidewalls of the first mandrel layer, wherein the first spacer layer comprises a doped silicon material. The first mandrel layer is selectively removed while keeping the first spacer layer. A second spacer layer is conformally formed on sidewalls of the first spacer layer and selectively removing the first spacer layer while keeping the second spacer layer.
Control profile
Chao Li from Duluth, GA, age ~65 Get Report