Transit Techies #35: Aaron Gordon, Surya Mattu, Marie Patino / Elif Ensari

This will be Transit Techies NYC's final session of the year, and we have some amazing speakers to look forward to. Talks will start at 6:30pm, and we'll mingle over light bites and refreshments before and afterwards.

Please sign up on NYU CUSP's Luma event for building access!

Speakers

Aaron Gordon, Surya Mattu, and Marie Patino are reporters at Bloomberg News.

"NJ Transit Is NYC’s Least Reliable Commuter Rail — By a Long Shot"

NJ Transit, Metro-North, and the LIRR are crucial arteries into Manhattan, moving hundreds of thousands of commuters into the Financial District and Midtown every day. As New York City faces a housing affordability crisis, the railroads are critical to the city’s future as the region seeks to build more densely near train stops. But one of those commuter railroads, NJ Transit, is significantly less reliable than the others. To understand the frequency of significant delays on New York commuter lines, Bloomberg tracked more than 190,000 trains this summer using live transit feeds, the kind used by navigation apps such as Google Maps. The results show NJ Transit riders had more issues than their New York and Connecticut counterparts. About one in every 18 NJ Transit trains was delayed by at least 15 minutes or canceled completely in May, June and July. For an average commuter, that meant a bad commute roughly every two weeks, versus once every three months or more on the more reliable lines to New York and Connecticut suburbs.

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Elif Ensari is a Research Scholar at NYU’s Marron Institute of Urban Management, where she works with the Transportation and Land Use group. Her research focuses on the costs of building passenger rail, ridership estimation, transit-oriented development, and New York City’s walking and cycling infrastructure.

Elif will present “Eye in the Sky: Harnessing AI to Monitor Police Response to Illegal Parking Complaints,” co-authored with Benjamin Arnav. Illegal parking clogs travel lanes, worsens gridlock, and blocks critical infrastructure, yet enforcement remains inconsistent. Using artificial intelligence and New York City DOT’s public camera feeds, the team developed an automated system to file 311 complaints and monitor police responses citywide. Their analysis revealed that over half of complaints were closed while vehicles remained illegally parked, and that only 3% resulted in tickets. These findings expose major enforcement gaps and point to the potential of automated ticketing and smarter street design to address chronic violations.

Please sign up on NYU CUSP's Luma event for building access!

The event will be held at 370 Jay Street, Brooklyn, NY in Room 1201. We hope to see you there!