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Jeremy A Karp, 37550 Davis St UNIT 31, San Francisco, CA 94111

Jeremy Karp Phones & Addresses

San Francisco, CA   

Pittsburgh, PA   

1615 Commonwealth Ave #8, Brighton, MA 02135   

Orinda, CA   

415 South St, Waltham, MA 02453   

Washington, DC   

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Jeremy A Karp

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Work

Company: Lyft Oct 2017 Position: Research scientist

Education

Degree: Doctorates, Doctor of Philosophy School / High School: Carnegie Mellon University 2012 to 2017 Specialities: Philosophy

Skills

Research • Data Analysis • Mathematica • Machine Learning • Game Theory • Stata • Sas • Python • Algorithms • Optimization • Statistics • Operations Research • Econometrics • Analysis • Java • Matlab • Economics • Quantitative Analytics • R • Statistical Modeling • Data Mining • Forecasting • Bayesian Inference

Interests

Approximation Algorithms • Network Design • Combinatorics • Theoretical Computer Science • Probability Theory • See 1 • Online Algorithms • See Less • Machine Learning • Stochastic Processes • Graph Theory • Game Theory • Graph Algorithms

Industries

Internet

Mentions for Jeremy A Karp

Jeremy Karp resumes & CV records

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Jeremy Karp Photo 19

Research Scientist

Location:
1324 Willard St, San Francisco, CA 94117
Industry:
Internet
Work:
Lyft
Research Scientist
Carnegie Mellon University May 2016 - Jun 2016
Instructor
Amazon May 2015 - Aug 2015
Research Scientist Intern
Cornerstone Research Sep 2010 - Jun 2012
Analyst
Lecg Jun 2009 - Aug 2009
Intern
Decision Resources Group Sep 2008 - May 2009
Consulting Intern
Education:
Carnegie Mellon University 2012 - 2017
Doctorates, Doctor of Philosophy, Philosophy
Carnegie Mellon University 2012 - 2014
Masters
Columbia University In the City of New York 2010 - 2010
Brandeis University 2006 - 2010
Bachelors, Bachelor of Arts, Economics, Mathematics, Psychology
Miramonte High School 2002 - 2006
Skills:
Research, Data Analysis, Mathematica, Machine Learning, Game Theory, Stata, Sas, Python, Algorithms, Optimization, Statistics, Operations Research, Econometrics, Analysis, Java, Matlab, Economics, Quantitative Analytics, R, Statistical Modeling, Data Mining, Forecasting, Bayesian Inference
Interests:
Approximation Algorithms
Network Design
Combinatorics
Theoretical Computer Science
Probability Theory
See 1
Online Algorithms
See Less
Machine Learning
Stochastic Processes
Graph Theory
Game Theory
Graph Algorithms

Publications & IP owners

Us Patents

Utilizing Throughput Rate To Dynamically Generate Queue Request Notifications

US Patent:
2021030, Sep 30, 2021
Filed:
Mar 31, 2020
Appl. No.:
16/836331
Inventors:
- San Francisco CA, US
Nir Even Chen - Redwood City CA, US
Dean Israel Grosbard - Albany CA, US
Jeremy Alexander Karp - San Francisco CA, US
Manu Singh Sabherwal - San Francisco CA, US
Lily Sierra - San Francisco CA, US
International Classification:
H04L 12/863
H04L 12/801
H04L 12/26
G06F 3/0481
G06Q 50/30
G06Q 10/02
Abstract:
The present disclosure relates to systems, non-transitory computer-readable media, and methods for dynamically controlling requestor device queues by monitoring and utilizing the throughput rate of matched provider devices and requestor devices. In some embodiments, the disclosed systems determine throughput rate of matched provider devices and requestor devices in real-time and/or predicts throughput rate utilizing historical features of a particular location. The disclosed systems can generate and provide queue request notifications to requestor devices based on a throughput rate at the location. Specifically, the disclosed systems can monitor a current queue status over time, compare the queue status to a queue threshold, and dynamically generate queue request notifications that reflects throughput-based queue modifiers as the current queue status approaches the queue threshold.

Systems And Methods For Queueing In Dynamic Transportation Networks

US Patent:
2020000, Jan 2, 2020
Filed:
Jun 29, 2018
Appl. No.:
16/024451
Inventors:
- San Francisco CA, US
Jianzhe Luo - Bellevue WA, US
Christopher Sholley - San Francisco CA, US
Adam Greenhall - Seattle WA, US
Jeremy Alexander Karp - San Francisco CA, US
International Classification:
G06Q 10/06
Abstract:
The disclosed computer-implemented method may include matching transportation requests to transportation providers using a dynamic transportation matching system. Matching transportation requestors which have varying preferences for waiting times and transportation pricing with transportation providers having varying levels of available supply may involve matching methods that satisfy the transportation requestors while maintaining an appropriate level of supply. A method which provides immediate service for transportation requestors that may be willing to pay a premium fare while placing transportation requestors not willing to pay a premium fare and may be willing to wait may provide a balance of supply and demand of transportation providers. Accordingly, immediately matching transportation requestors not willing to wait while placing the transportation requestors willing to wait in a queue may provide the balanced approach to managing transportation provider availability. Other methods, systems, and computer-readable media are disclosed.

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