Professional Records
License Records
Francis N Ebong
License #:
HHA8847 - Active
Category:
NURSING
Issued Date:
Jan 11, 2013
Expiration Date:
Oct 30, 2017
Type:
HOME HEALTH AIDE
Francis Ebong Phones & Addresses
-
1681 Fulton St APT 1, San Francisco, CA 94117
-
1770 Pacific Ave APT 201, San Francisco, CA 94109
Work
Company:
X: the moonshot factory Jan 2019
Position:
Eir
Education
Degree:
Master of Business Administration, Masters
School / High School:
Gw Investment Institute 2006 to 2008
Skills
Strategy • Business Strategy • Leadership • Supply Chain Management • Cross Functional Team Leadership • Program Management • Management Consulting • Supply Chain • Operations Management • Strategic Planning • Product Development • Business Process Improvement • Team Leadership • Contract Negotiation • Forecasting • Financial Modeling • Strategic Partnerships • Strategic Sourcing • Logistics • Process Improvement • Deal Closure • Operational Excellence • Supply Management • Executive Leadership • Sql
Languages
English
Industries
Internet
Resumes
Resumes
Francis Ebong
View pageLocation:
1681 Fulton St, San Francisco, CA 94117
Industry:
Internet
Work:
X: the Moonshot Factory
Eir
Synqq
Advisory Board Member
Facebook Nov 2015 - Dec 2017
Director, Global Operations and Partnerships
Postmates Oct 2014 - Oct 2015
Director, Business and Operations
Apple Aug 2011 - Sep 2014
Global Business Operations
Eir
Synqq
Advisory Board Member
Facebook Nov 2015 - Dec 2017
Director, Global Operations and Partnerships
Postmates Oct 2014 - Oct 2015
Director, Business and Operations
Apple Aug 2011 - Sep 2014
Global Business Operations
Education:
Gw Investment Institute 2006 - 2008
Master of Business Administration, Masters United States Naval Academy 1999 - 2003
Bachelors, Bachelor of Science, Computer Science, General Science, Engineering, Physics
Master of Business Administration, Masters United States Naval Academy 1999 - 2003
Bachelors, Bachelor of Science, Computer Science, General Science, Engineering, Physics
Skills:
Strategy
Business Strategy
Leadership
Supply Chain Management
Cross Functional Team Leadership
Program Management
Management Consulting
Supply Chain
Operations Management
Strategic Planning
Product Development
Business Process Improvement
Team Leadership
Contract Negotiation
Forecasting
Financial Modeling
Strategic Partnerships
Strategic Sourcing
Logistics
Process Improvement
Deal Closure
Operational Excellence
Supply Management
Executive Leadership
Sql
Business Strategy
Leadership
Supply Chain Management
Cross Functional Team Leadership
Program Management
Management Consulting
Supply Chain
Operations Management
Strategic Planning
Product Development
Business Process Improvement
Team Leadership
Contract Negotiation
Forecasting
Financial Modeling
Strategic Partnerships
Strategic Sourcing
Logistics
Process Improvement
Deal Closure
Operational Excellence
Supply Management
Executive Leadership
Sql
Languages:
English
Publications
Us Patents
Adaptively Adjusting Parameters Of Equipment Operating In Unpredictable Terrain
View pageUS Patent:
20230102576, Mar 30, 2023
Filed:
Sep 27, 2021
Appl. No.:
17/485928
Inventors:
- Mountain View CA, US
Gabriella Levine - San Francisco CA, US
Elliott Grant - Woodside CA, US
Daniel Ribeiro Silva - San Jose CA, US
Linda Kanu - Pleasanton CA, US
Francis Ebong - San Francisco CA, US
Gabriella Levine - San Francisco CA, US
Elliott Grant - Woodside CA, US
Daniel Ribeiro Silva - San Jose CA, US
Linda Kanu - Pleasanton CA, US
Francis Ebong - San Francisco CA, US
International Classification:
A01B 79/00
A01B 63/00
G06K 9/00
G06N 3/02
A01B 63/00
G06K 9/00
G06N 3/02
Abstract:
Implementations are disclosed for adaptively adjusting various parameters of equipment in unpredictable terrain, such as agricultural fields. In various implementations, edge computing device(s) may obtain a first image captured by vision sensor(s) transported across an agricultural field by a vehicle. The first image may depict plant(s) growing in the agricultural area. The edge computing device(s) may process the first image based on a machine learning model to generate agricultural inference(s) about the plant(s) growing in the agricultural area. The edge computing device(s) may determine a quality metric for the agricultural inference(s). While the vehicle continues to travel across the agricultural field, and based on the quality metric: the edge computing device(s) may trigger one or more hardware adjustments to one or more of the vision sensors, or one or more adjustments in an operation of the vehicle.