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Jody M Kelman

from San Francisco, CA
Age ~42
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Related to:
Islami P Segatol, 78Roshan L Islami, 43Parvaneh S Islami
Connected to:
Faye A Kelman, 76Gerry K Kelman, 77Gregg E Kelman, 59Hayley Kelman, 54Howard M Kelman, 73Jacob Kelman, 31Jennifer S Kelman, 48Pamela C Kelman, 38Sharon M Kelman, 77Susan L Kelman, 82

Jody Kelman Phones & Addresses

  • San Francisco, CA
  • Mill Valley, CA
  • Washington, DC
  • 185 Elm St, Concord, MA 01742 (978) 369-9193
  • Cambridge, MA

Resumes

Resumes

Jody Kelman Photo 1

Director Of Product And Program Management, Self-Driving Platform

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Location:
854 Capp St, San Francisco, CA 94110
Industry:
Internet
Work:
Lyft
Director of Product and Program Management, Self-Driving Platform
Serena & Lily 2013 - 2015
Strategy, Analysis, and Planning
Dc Promise Neighborhood Initiative, Inc 2011 - 2012
Fellow
Mckinsey & Company 2008 - 2010
Consultant
Presidential Transition Team Dec 2008 - Jan 2009
Member, Technology, Innovation, and Government Reform Team
Education:
University of Sydney 2007 - 2008
Masters, Master of Arts, International Relations Harvard University 2001 - 2005
Bachelors, Bachelor of Arts, Social Studies
Skills:
Strategy
Politics
Start Ups
Marketing
Strategic Communications
Competitive Analysis
Analysis
E Commerce
Team Leadership
Strategic Partnerships
Social Media
Analytics
Financial Modeling
Management Consulting
Leadership
Interests:
Human Rights
Economic Empowerment
Languages:
English
Jody Kelman Photo 2

Jody Kelman

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Publications

Wikipedia

Massachusetts Board of Educati

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Jody Kelman Jeff DeFlavio, Chair Emeritus, State Student Advisory Council Andrew "AJ" Fajnzylber, Chair Emeritus, State Student Advisory Council ...

Isbn (Books And Publications)

Western Europe

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Author

Jody M. Kelman

ISBN #

0312348908

Us Patents

Dynamic Autonomous Vehicle Servicing And Management

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US Patent:
20200302567, Sep 24, 2020
Filed:
Jun 8, 2020
Appl. No.:
16/895952
Inventors:
- San Francisco CA, US
Jody Kelman - San Francisco CA, US
International Classification:
G06Q 50/30
G08G 1/00
G01C 21/34
G06Q 10/06
Abstract:
In one embodiment, a method includes determining, based on vehicle status information associated with a vehicle, that the vehicle is to be serviced at a service facility. The method includes identifying multiple routes between a current location of the vehicle and the service facility. Each of the multiple routes includes a multiple road segments that connect the current location to the service facility. The method includes selecting a route from the multiple routes based at least on the vehicle status information associated with the vehicle and at least one condition associated with one or more of the road segments of each of the multiple routes. The method includes instructing the vehicle to travel from the current location to the service facility along the selected route.

Dynamic Modeling And Simulation Of An Autonomous Vehicle Fleet Using Real-Time Autonomous Vehicle Sensor Input

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US Patent:
20200126417, Apr 23, 2020
Filed:
Sep 5, 2019
Appl. No.:
16/562210
Inventors:
- San Francisco CA, US
Nicholas Chamandy - San Francisco CA, US
Jody Kelman - San Francisco CA, US
International Classification:
G08G 1/123
G06Q 50/30
G01C 21/00
G05B 17/02
G05D 1/00
G05D 1/02
Abstract:
Embodiments provide techniques for autonomous vehicle fleet modeling and simulation, such as within a dynamic transportation matching system utilizing one or more vehicle types such as non-autonomous vehicles and autonomous vehicles. An autonomous fleet simulation model may be generated based on real-world parameters of an autonomous vehicle fleet, and the parameters may be modified in a simulation in order to determine optimized values that may be applied to the real-world autonomous vehicle fleet.

Dynamic Modeling And Simulation Of An Autonomous Vehicle Fleet Using Real-Time Autonomous Vehicle Sensor Input

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US Patent:
20190011931, Jan 10, 2019
Filed:
Jul 10, 2017
Appl. No.:
15/645776
Inventors:
- San Francisco CA, US
NICHOLAS CHAMANDY - San Francisco CA, US
JODY KELMAN - San Francisco CA, US
International Classification:
G05D 1/02
G05D 1/00
G05B 17/02
Abstract:
Embodiments provide techniques for autonomous vehicle fleet modeling and simulation, such as within a dynamic transportation matching system utilizing one or more vehicle types such as non-autonomous vehicles and autonomous vehicles. An autonomous fleet simulation model may be generated based on real-world parameters of an autonomous vehicle fleet, and the parameters may be modified in a simulation in order to determine optimized values that may be applied to the real-world autonomous vehicle fleet.

Dynamic Autonomous Vehicle Matching Optimization

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US Patent:
20180315146, Nov 1, 2018
Filed:
Apr 27, 2017
Appl. No.:
15/499527
Inventors:
- San Francisco CA, US
Jody Kelman - San Francisco CA, US
International Classification:
G06Q 50/30
G06Q 10/06
G01C 21/34
Abstract:
Embodiments provide techniques for autonomous vehicle management. In an embodiment, service requests are received and a set of service providers responsive to the request are determined. For example, a set of service providers that are eligible to be matched to the service request may be comprised of autonomous and non-autonomous vehicles. The set of service providers are matched to the request based on various factors such as a match score based on at least a location factor and a weighting factor.

Dynamic Autonomous Vehicle Servicing And Management

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US Patent:
20180308191, Oct 25, 2018
Filed:
Apr 25, 2017
Appl. No.:
15/496913
Inventors:
- San Francisco CA, US
Jody Kelman - San Francisco CA, US
International Classification:
G06Q 50/30
G08G 1/00
G01C 21/34
G05D 1/02
G01C 21/36
G06Q 10/06
Abstract:
Embodiments provide techniques for autonomous vehicle management. When a service request (e.g., ride request, maintenance request, idling request, etc.) is received, the service request may be matched with an appropriate service provider (e.g., an autonomous vehicle to a rider, a maintenance facility to an autonomous vehicle, etc.). An autonomous vehicle may be then be dispatched based on the service request. For example, the autonomous vehicle may be dispatched to a pickup location associated with a ride request. Similarly, the autonomous vehicle may be dispatched to a maintenance facility in response to receiving a maintenance request. The maintenance request may be triggered after applying one or more thresholds and/or rules to the autonomous ride data collected from the autonomous vehicle. As autonomous ride data is collected from various autonomous vehicles, it can be analyzed to determine traffic patterns, road conditions, or other data.
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Jody M Kelman from San Francisco, CA, age ~42 Get Report