Connected Cities with Smart Transportation
Instructor: Tu Lan & Vivaldi Rinaldi, New York University Beginner level: No prior experience required. Schedule: Friday, October 11, 1:00 pm – 2:00 pm ET Description: Drones are becoming an
Instructor: Irving Fang, New York University Beginner level: No prior experience required. Schedule: Wednesday, Oct 23th, 2024 1:00 PM - 2:00 PM Description: In the talk, we will discuss some
TransportationCamp NYC will be held on Saturday, October 26th at NYU's Tandon School of Engineering in Downtown Brooklyn. Join us to discuss all things transportation and connect with professionals, students,
Instructor: Tao Li, New York University Beginner level: No prior experience required. Basic optimization knowledge would be helpful but not required. Description: Urban transportation networks are complex and dynamic, and
Instructor: Yanchao Li, New York University Beginner level: No prior experience required. Schedule: Friday, Nov 15th, 2024 1:00 PM - 2:00 PM Description: In this course, we will discuss the
You are cordially invited to El Puente for a gathering to listen together to oral histories from elders and youth in communities across Brooklyn and Queens. Oral history facilitators Mitra Bonshahi and Adriana Gallardo
This engaging event will take place on December 11th at 5pm, concluding with a cocktail reception, where you can connect with industry leaders and peers. During the conference, we’ll explore
The ubiquity of GPS-equipped mobile devices has enabled the collection of human mobility data with high spatiotemporal granularity. Indeed, there now exists an ecosystem of both data providers and consulting
This year's panelists are Dr. Semiha Ergan, Professor at NYU; Geline Canayon, Senior Project Manager at Aimsun & Vice President of ITE MET Section; and Alia Kasem, Senior Data Scientist at NYC
In this seminar, I will introduce GPUDrive, a high-performance, data-driven driving simulator that operates at 1 million FPS. GPUDrive is built on the Madrona Game Engine and uses GPU acceleration
Abstract: In this course, we will discuss the decision theory of random utility maximization and discrete choice models (DCMs) including multinomial logit (MNL), nested logit (NL), mixed logit (MXL), and