Intro 144B (Uber) Study
Contributed to a landmark study on For-Hire Vehicles (FHVs) in New York City, focusing on platforms such as Uber, Lyft, Via, and Juno.
Assisted in processing and analyzing large-scale datasets—including FHV and taxi trips, driver and rider pay, GPS traces, and logon/logoff records—using Python and Tableau.
Supported the development of an economic model to estimate the policy impacts on traffic congestion, driver earnings, wait times, and regulatory revenue.
Collaborated with the project lead in preparing technical materials for stakeholder briefings, including a presentation to Deputy Mayor Anglin.
The study informed NYC’s historic 2019 regulations aimed at reducing Manhattan congestion and improving FHV driver wages.
Sep 26, 2018
