Events

Upcoming Events

Dec
9
Mon
Better Buses: Advancing Social Equity for New Yorkers: How Can Improved Bus Service Transform Economic Opportunity @ Kimmel Center for University Life
Dec 9 @ 9:30 am – 11:00 am

You are invited to an NYU Rudin Center for Transportation forum:

“Better Buses: Advancing Social Equity for New Yorkers:  How Can Improved Bus Service Transform Economic Opportunity”

The panelists are:

Polly Trottenberg, Commissioner, NYC Department of Transportation
David Jones, President and Chief Executive Officer, Community Service Society
Patrick McClellan, State Policy Director, New York League of Conservation Voters

The moderator is: Sarah M. Kaufman, Associate Director, NYU Rudin Center for Transportation

Click the below link to register to attend (required):

 

 

Dec
10
Tue
Subway Signaling Innovation Summit @ New York University Kimmel Center
Dec 10 @ 9:00 am – 12:00 pm

C2SMART Professor Joseph Chow will be joining the Signaling Innovation Summit as a tech pitch evaluator. This Summit will bring together innovators, stakeholders and academic experts to create partnerships that improve subway safety, performance and operational efficiency through signaling modernization.

The summit will begin at 9:00am with breakfast and networking, followed by presentations on signaling program goals and industry opportunities, and end at approximately 12:00pm with a workshop on modernizing procurement and R&D at the MTA.

 

 

Dec
11
Wed
Seminar: Zhiding Yu, Towards Weakly-Supervised Visual Understanding @ C2SMART Center Conference Room
Dec 11 @ 12:00 pm – 1:00 pm
Abstract:

Learning with weak and self-supervisions recently emerged as compelling tools towards leveraging vast amounts of unlabeled or partially-labeled data. In this talk, I will present some of the latest advances in weakly-supervised visual scene understanding from NVIDIA. Specifically, I will summarize and discuss some challenges and potential solutions in weakly-supervised learning, and introduce our works mainly from three directions: 1. learning with Inaccurate supervision, 2. learning with Incomplete supervision, and 3. learning with Inexact supervision. I will talk about specific works and applications that are aligned with these directions, including semantic boundary detection under noisy annotations, unsupervised domain adaptation, person re-id and weakly-supervised object detection, with their applications in autonomous driving, robotics, medical imaging and AI city.

Bio:

Zhiding Yu joined NVIDIA Research as a Research Scientist in 2018. Before that, he obtained Ph.D. degree in ECE from Carnegie Mellon University in 2017. His research interests mainly focus on deep representation learning, weakly/semi-supervised learning, transfer learning and deep structured prediction, with their applications to: (1) general scene/video understanding, (2) bottom-up perceptual grouping and mid-level vision, (3) robust representation for cross-domain/cross-task/open-set generalization and adaptation, (4) learning with interactive weak supervisions. He is a winner of the Domain Adaptation for Semantic Segmentation Challenge in Workshop on Autonomous Driving (WAD), CVPR18. He is a co-author of the best student paper in ISCSLP14, and the winner of the best paper award in WACV15. He was twice the recipient of the HKTIIT Post-Graduate Excellence Scholarships in 2010 and 2012. His intern work on deep facial expression recognition at Microsoft Research won first runner-up at the EmotiW-SFEW Challenge 2015 and was integrated into the Microsoft Emotion Recognition API under the Microsoft Azure Cognitive Services.

 

Watch Seminar Here

 

Jan
17
Fri
Shared on-demand automated vehicles for first/last mile transit and beyond @ C2SMART Center Conference Room
Jan 17 @ 2:30 pm – 3:00 pm
Abstract:

In this presentation Gonçalo will talk about recent developments from TU Delft research about the usage of automated vehicles as part of public transport networks. The research objectives, methods and results will be discussed in a critical perspective with the main goal of understanding what challenges we still face with understanding the role of automated driving as part of future urban transportation systems. Rather than giving final conclusions this presentation is meant to act as a spark for this much needed discussion. The talk will particularly focus on the usage of AVs as first/last mile connection in transit trips but it will also look at SAVs for door-to-door transport.

Bio:

Gonçalo H. A. Correia is an assistant professor in multi-modal urban transport networks at the Department of Transport & Planning, TU Delft. His research focuses on transport demand management through the study of integrated transportation, intelligent transport systems, travel behavior change and land use interactions. He uses mainly optimization, simulation, and theory of utility maximization for analyzing, testing and forecasting transport networks supply and demand. He is currently working on unraveling the future with automated vehicles, especially on urbanized regions. He has published more than 40 research papers in top scientific journals and he is part of the editorial board of several transportation science journals including transportation research part C: emerging technologies and transportation research Part E: logistics and transportation review. He advises several companies and institutions on the future of mobility and he is an international speaker on the impacts of mobility innovations. Gonçalo co-directs the hEAT lab (research on electric and automated transport) that is part of the Department of Transport & planning at TU Delft.

Feb
25
Tue
Mobility Technologies for People with Disabilities @ NYU Tandon School of Engineering
Feb 25 all-day
Mobility Technologies for People with Disabilities @ NYU Tandon School of Engineering

POSTPONED TO 2/25/2020

 

This event will highlight new technologies and advances from startups and industry targeted at improving mobility for people with disabilities. Stay tuned for more information.

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