Connected Cities for Smart Mobility toward Accessible and Resilient Transportation
Instructor: Fan Zuo, New York University Schedule: Friday March 10, 11:00am-12:00pm Description: In this course, you will learn about ChatGPT, a state-of-the-art language model developed by OpenAI. You will gain
Graph Neural Networks (GNNs) are a powerful tool for analyzing and processing graph-structured data. This course covers the basics of GNNs, including graph convolutional networks, graph attention networks and graph wavelet networks, including how they work and how to implement them. The session aims to provide a solid understanding of GNN modeling for machine learning practitioners, data scientists, and anyone interested in AI advancements.
The C2SMART Center and the NYU chapter of the Institute of Transportation Engineers (ITE) are excited to host our annual Women in Transportation Panel Discussion, including an opportunity for attendees to network and socialize. This year's panel boasts three amazing women working in the transportation industry who will share their perspectives and experiences.
In this hands-on course, you’ll learn how to use Unity 3D to build 3D models of road networks. You’ll start with the basics of Unity 3D, including its interface, GameObjects, components, and scripting. From there, you’ll dive into building 3D models of road networks, covering elements such as roads, buildings, and terrain.
This course covers the basics of graph neural networks (GNNs), including graph convolutional networks, graph attention networks and graph wavelet networks. The session aims to provide a solid understanding of GNN modeling for machine learning practitioners, data scientists, and anyone interested in AI advancements.
In this course, you will learn how to harness the power of OSMnx, a Python library for extracting and visualizing Open Street Maps data. Through hands-on exercises, you will gain practical experience in using OSMnx to model and simulate projects and have a solid understanding of this Python library and be able to apply OSMnx to real-world problems.
This presentation introduces a deep choice framework that synergizes DNNs and DCMs to model individual travel decision.
We show how to stabilize a polynomial reaction diffusion system using boundary control, integration by parts, completing the square and an infinite dimensional extension of Al'brekht's method. Presented by Alfred
C2SMARTER welcomes new and returning transportation students to the Fall 2023 academic year with a kick-off event. Learn about C2SMARTER, meet the faculty, and see the space. Come learn more
Instructor: Haggai D. Davis, III, New York University Hands-on exercise: Yes Beginner level: No prior experience required. Schedule: Friday Oct 13th, 11:30am-12:30pm Description: Machine learning is an incredibly broad term
Instructor: Vidisha Chowdhury, University of Pennsylvania & Philippe Schicker, Carnegie Mellon University Hands-on exercise: Yes Beginner level: No prior experience required. Schedule: Friday October 20th, 12-1 pm Description: Google Earth
Instructor: Yuhao Liu, NYU Shanghai Hands-on exercise: Yes Beginner level: No prior experience required. Schedule: Friday Oct 27th, 12-1pm Description: This course is designed to equip the audience with the