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BEGIN:VEVENT
DTSTART;TZID=America/New_York:20260414T123000
DTEND;TZID=America/New_York:20260414T133000
DTSTAMP:20260429T082849
CREATED:20260410T130857Z
LAST-MODIFIED:20260410T130857Z
UID:90748-1776169800-1776173400@c2smart.engineering.nyu.edu
SUMMARY:Morphing Structures for Civil Engineering\, from Gridshells to Burrowing Robots
DESCRIPTION:Shape-morphing metamaterials\, mechanical systems and structures are designed to predictably achieve large shape changes when actuated. While pervasive in aerospace and mechanical engineering\, these systems are seldom considered in civil engineering applications. This talk will concentrate on the morphing mechanics of some of the structures designed in our lab\, highlighting some of their potential civil applications. \nFirst\, we will present a strategy to turn flat arrangements of structural elements into pop-up domes\, investigating their deployment mechanics\, load-bearing capacity and comparing them to existing structures such as gridshells. Then\, we will illustrate how morphing structures can serve as the backbone of burrowing robots for geotechnical engineering applications\, where they need to engage in complex interactions with surrounding soils.
URL:https://c2smart.engineering.nyu.edu/event/morphing-structures-for-civil-engineering-from-gridshells-to-burrowing-robots/
LOCATION:C2SMART Center Viz Lab\, 6 Metrotech Center\, Room 460\, Brooklyn\, 11201
CATEGORIES:Seminars,Student Events
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20260408T173000
DTEND;TZID=America/New_York:20260408T190000
DTSTAMP:20260429T082849
CREATED:20260324T161026Z
LAST-MODIFIED:20260326T180459Z
UID:90686-1775669400-1775674800@c2smart.engineering.nyu.edu
SUMMARY:Women in Transportation 2026
DESCRIPTION:
URL:https://c2smart.engineering.nyu.edu/event/women-in-transportation-2026/
CATEGORIES:Seminars,Student Events
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20260109T140000
DTEND;TZID=America/New_York:20260109T150000
DTSTAMP:20260429T082849
CREATED:20251201T170925Z
LAST-MODIFIED:20251201T170925Z
UID:90461-1767967200-1767970800@c2smart.engineering.nyu.edu
SUMMARY:Seminar: A Large-scale Simulation Platform and AI-driven Operational Strategies for On-demand Ride Services
DESCRIPTION:Abstract: In this work\, we develop a novel multi-functional and open-sourced simulation platform for on-demand ride service operations\, which can simulate the behaviors and movements of various agents (including drivers and passengers) on a real transportation network. It provides a few accessible portals for users to train and test various optimization algorithms\, especially reinforcement learning algorithms\, for a variety of tasks\, including on-demand matching\, idle vehicle repositioning\, and dynamic pricing. Evaluated by experiments based on real-world datasets\, the simulator is demonstrated to be an efficient and effective test bed for various tasks related to on-demand ride service operations. \nBio: Dr. Jintao Ke is an Assistant Professor in the Department of Civil Engineering at the University of Hong Kong (HKU). Dr. Ke received his B.S. degree (2016) in Civil Engineering from Zhejiang University\, and his PhD degree (2020) in Civil and Environment Engineering from Hong Kong University of Science and Technology. His research interests include on demand mobility services\, transportation big data analytics\, multimodal transportation system optimization\, transportation pricing\, spatiotemporal traffic prediction\, etc. He has published more than 50 SCI/SSCI indexed research papers in top-tier journals in the field of transportation research and data mining\, such as Transportation Research Part A-F\, IEEE Transactions on\nIntelligence Transportation System\, IEEE Transactions on Knowledge and Data Engineering\, IEEE Internet of Things\, Computer-Aided Civil and Infrastructure Engineering. He has been ranked as the World's Top 2% most-cited scientists by Stanford University since 2023. He is serving as an Editorial Board Member of Transportation Research Part C\, Transportation Research Part E\, and Travel Behavior and Society.
URL:https://c2smart.engineering.nyu.edu/event/seminar-a-large-scale-simulation-platform-and-ai-driven-operational-strategies-for-on-demand-ride-services/
LOCATION:C2SMART Center Viz Lab\, 6 Metrotech Center\, Room 460\, Brooklyn\, 11201
CATEGORIES:Seminars,Student Events
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20251202T123000
DTEND;TZID=America/New_York:20251202T143000
DTSTAMP:20260429T082849
CREATED:20251107T191349Z
LAST-MODIFIED:20251107T191420Z
UID:90272-1764678600-1764685800@c2smart.engineering.nyu.edu
SUMMARY:AECOM Fireside Chat & Panel
DESCRIPTION:
URL:https://c2smart.engineering.nyu.edu/event/cmaa/
LOCATION:C2SMART Center Viz Lab\, 6 Metrotech Center\, Room 460\, Brooklyn\, 11201
CATEGORIES:Seminars,Student Events
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20251120T140000
DTEND;TZID=America/New_York:20251120T150000
DTSTAMP:20260429T082849
CREATED:20251020T191118Z
LAST-MODIFIED:20251120T173151Z
UID:89969-1763647200-1763650800@c2smart.engineering.nyu.edu
SUMMARY:Seminar: AI-empowered Digital Twin for Traffic Safety Analysis
DESCRIPTION:Abstract: Traffic safety research faces the paradox of rarity—the most critical crashes occur so infrequently that passive methods relying on historical records cannot accurately estimate traffic risks. This talk first reviews current methodologies and highlights their limitations in handling rare\, high-risk events. Building on these insights\, we chart a new path that fuses active safety analysis of near-miss events and generative AI. As a preliminary foundation for the generative AI–enabled safety analysis\, our recent work provides digital-twin–enabled active safety analysis through three pivotal components: (1) a physics-grounded active safety module that identifies near-miss events across diverse traffic contexts; (2) group-wise interaction modeling that captures multi-agent behaviors in traffic; and (3) a high-fidelity digital twin integrating detailed vehicle dynamics\, tire–road interaction\, and the above active-safety and interaction models. Together\, these elements enable proactive risk prevention\, expanding safety analysis beyond observed outcomes to the full spectrum of what could happen\, and lay the foundation for Vision Zero.\n\nBio: Dr. Yang Zhou is an assistant professor in the Zachry Department of Civil and Environmental Engineering at Texas A&M University\, and career initiation fellow of Texas A&M Institute of data science. He received his Ph.D. degree and Master degree from the University of Wisconsin-Madison and the University of Illinois at Urbana and Champaign\, respectively. Before joining Texas A&M\, Yang worked as a postdoctoral research associate supported by the Department of Civil and Environmental Engineering\, University of Wisconsin-Madison.  Yang has over ten years of experience in connected automated vehicle control and analysis\, traffic flow analysis\, AI applications on transportation\, and high-fidelity simulation. Yang has PIed multiple federal and local grants such as FHWA-EAR and SS4A. Yang has published more than 70 top-tier transportation journals\, including Transportation Research Part B\, Transportation Research Part C\, and IEEE Transactions on Intelligent Transportation Systems.
URL:https://c2smart.engineering.nyu.edu/event/seminar-ai-empowered-digital-twin-for-traffic-safety-analysis/
LOCATION:C2SMART Center Viz Lab\, 6 Metrotech Center\, Room 460\, Brooklyn\, 11201
CATEGORIES:Seminars,Student Events
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20251118T123000
DTEND;TZID=America/New_York:20251118T133000
DTSTAMP:20260429T082849
CREATED:20251105T182735Z
LAST-MODIFIED:20251117T163854Z
UID:90266-1763469000-1763472600@c2smart.engineering.nyu.edu
SUMMARY:CUE Distinguished Seminar Series: Simulating the Physical and the Connected: Neural Models for Structures and Networks
DESCRIPTION:Advances in machine learning are transforming how we model and design engineered systems\, from industrial components to large-scale infrastructure networks. This seminar presents recent developments in physics-based neural networks and neural operators for fast\, accurate physics-based simulation. The first part focuses on individual structures and introduces models that accelerate design computations and improve generalization across geometries and parameters. The second part focuses on graph neural network (GNN) models for infrastructure networks and their use in developing digital twins of transportation systems. These GNNs enable rapid computation of network metrics—such as shortest paths\, connectivity\, and dynamic traffic flows—and can incorporate physics constraints like travel demand influence and flow conservation for enhanced accuracy and consistency. Case studies on urban networks demonstrate how such models can support resilient and data-driven decision making for asset management\, mobility\, and emergency response. \nDr. Hadi Meidani is an Associate Professor in the Department of Civil and Environmental Engineering at the University of Illinois at Urbana-Champaign (UIUC). His research focuses on uncertainty quantification\, scientific and physics-informed machine learning\, and fast computational methods for infrastructure and engineering design. He earned his Ph.D. in Civil Engineering\, his M.S. in Electrical Engineering\, and his M.S. in Structural Engineering from the University of Southern California (USC). Prior to joining UIUC\, he was a postdoctoral scholar in the Department of Aerospace and Mechanical Engineering at USC and in the Scientific Computing and Imaging Institute at the University of Utah. Dr. Meidani is the Chair of the Machine Learning Committee of the ASCE Engineering Mechanics Institute. At UIUC\, he is the Founding Chair of the AI in CEE Task Force in his department. Dr. Meidani is the recipient of an NSF CAREER Award for his work on fast computational models for infrastructure networks.
URL:https://c2smart.engineering.nyu.edu/event/cue-distinguished-seminar-series-simulating-the-physical-and-the-connected-neural-models-for-structures-and-networks/
LOCATION:C2SMART Center Viz Lab\, 6 Metrotech Center\, Room 460\, Brooklyn\, 11201
CATEGORIES:Seminars,Student Events
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20251113T173000
DTEND;TZID=America/New_York:20251113T183000
DTSTAMP:20260429T082849
CREATED:20251105T145939Z
LAST-MODIFIED:20251111T220722Z
UID:90258-1763055000-1763058600@c2smart.engineering.nyu.edu
SUMMARY:C2SMART Career Panel
DESCRIPTION:Join us for a Career Panel featuring NYU’s Dr. Jingqin Gao & Holly Chase\, Suzana Duran Bernardes of Disney\, and Michael Willson of ARUP.  This panel will explore career trajectories\, lessons learned\, and helpful advice to students about to enter the job market. The panelists have an array of experiences from several industries and schools; come learn about their transitions from student to young professional to better inform your own path! \nModerated by ITE NYU Student Chapter Co-President Stephen Martone. Light refreshments will be provided\,
URL:https://c2smart.engineering.nyu.edu/event/c2smart-career-panel/
CATEGORIES:Seminars,Student Events
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20251112T130000
DTEND;TZID=America/New_York:20251112T140000
DTSTAMP:20260429T082849
CREATED:20251020T153149Z
LAST-MODIFIED:20251020T153518Z
UID:89965-1762952400-1762956000@c2smart.engineering.nyu.edu
SUMMARY:Seminar: Inverse Learning and Intervention of Transportation Network Equilibrium
DESCRIPTION:Abstract:\nBy 2035\, nearly half of all new vehicles in the United States will be connected\, generating unprecedented volumes of mobility data. Leveraging emerging connected mobility data\, this talk establishes an AI-enabled inverse learning framework to transform the transportation network equilibrium modeling paradigm\, which has been the foundation of system planning and management for over seventy years. \nTraditional transportation network equilibrium models are time-consuming and costly to calibrate. This talk presents the inverse learning of user equilibrium as a novel framework for constructing nonparametric\, context-dependent network equilibrium models directly from empirical travel patterns. We compare nonparametric and parametric approaches\, mathematically clarifying the trade-offs among behavioral realism\, data availability\, and computational cost. The proposed neural-network-based nonparametric framework can automatically discover any well-posed network equilibrium model given\nsufficient data\, without relying on predefined behavioral assumptions. In contrast\, the semi-parametric approach is more computationally tractable\, as it simplifies the inverse learning problem into a sequence of convex optimizations. \nFinally\, we apply the inverse learning framework to a long-term network design problem for the city of Ann Arbor\, Michigan. Using real-world crowdsourced data\, we learned a context-dependent equilibrium model and introduce a certified\, auto-differentiation-accelerated algorithm to solve the resulting distributionally robust bi-level network design problem under contextual uncertainty. \nBio:\nDr. Zhichen Liu is an Assistant Professor in the Stony Brook University Department of Civil Engineering. Her research focuses on innovating next-generation modeling and computational tools for mobility and logistics systems\, with an emphasis on connectivity\, electrification\, and automation. She received her Ph.D. in Civil Engineering and M.S. in Industrial and Operational Engineering from the University of Michigan\, and previously served as a Visiting Scientist at General Motors. Dr. Liu is a recipient of the Rackham Predoctoral Fellowship and was honored as the sole global awardee of the prestigious Helene M. Overly Memorial Scholarship by the WTS International Foundation.
URL:https://c2smart.engineering.nyu.edu/event/89965/
LOCATION:C2SMART Center Viz Lab\, 6 Metrotech Center\, Room 460\, Brooklyn\, 11201
CATEGORIES:Seminars,Student Events,Virtual Events,Webinars
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20251025T090000
DTEND;TZID=America/New_York:20251025T180000
DTSTAMP:20260429T082849
CREATED:20250910T160927Z
LAST-MODIFIED:20250918T210509Z
UID:89278-1761382800-1761415200@c2smart.engineering.nyu.edu
SUMMARY:transportationcamp 2025
DESCRIPTION:
URL:https://c2smart.engineering.nyu.edu/event/transportationcamp-2025/
CATEGORIES:Seminars,Student Events
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20251021T123000
DTEND;TZID=America/New_York:20251021T133000
DTSTAMP:20260429T082849
CREATED:20251008T162634Z
LAST-MODIFIED:20251008T162634Z
UID:89858-1761049800-1761053400@c2smart.engineering.nyu.edu
SUMMARY:Seminar: Self-driving Vehicles as Transit in US Settings: Complementing Buses and Trains with Demand-responsive SAVs
DESCRIPTION:ABSTRACT: Shared autonomous vehicles (SAVs) can deliver door-to-door (D2D)\, first-mile last-mile (FMLM) and dynamic ride-sharing (DRS or pooled-ride) services in many cities today. This 3-part presentation explores potential improvements in US travel and transit systems by simulating interactions between fixed-route and on-demand SAV services across the Chicago and Austin regions. The first study microsimulates SAVs providing fixed-route\, fixed-stop service alongside private automobiles. System costs for each traveler type are computed across different demand profiles\, SAV sizes (seat counts)\, and other dimensions; and smaller SAVs reduce corridor costs across most scenarios. \nThe second uses POLARIS to mesoscopically simulate D2D plus FMLM and autonomous-bus services across the 20-county Chicago region’s hundreds of train stations\, thousands of bus stops\, and millions of travelers. Assuming fares of $0.50 per passenger-mile and 1 SAV for every 40 residents\, this mode is predicted to attract 15% of person-trips and lower household vehicle ownership by 40%. Adding FMLM service raises the region’s traditional transit (bus + train) split from 5.4% to 6.3%\, with each SAV serving 12% more trip requests per day. Automating the bus system (and halving headways\, with half the seats per bus) does little to mode splits. The third study simulates a full replacement of buses with autonomous services across the 6-county Austin region. Using the region’s bus stops as pickup and drop-off points\, the transit fleet size falls by 10% or more\, thanks to coordination in trip services. Subsidizing SAV fleet managers to serve current bus demand emerges as the region’s most cost-effective and welfare-improving transit option. \nBIO: Kara Kockelman is a registered professional engineer and holds a PhD\, MS\, and BS in civil engineering\, a master’s in city planning\, and a minor in economics from the University of California at Berkeley. Dr. Kockelman has been a professor of transportation engineering at the University of Texas at Austin for 27 years\, and is Associate Site Director of the NSF Industry-University Cooperative Research Center for Efficient Vehicles and Sustainable Transportation Systems and an MIT Mobility Fellow. She has authored over 240 journal articles (and two books)\, and her primary research interests include planning for shared and autonomous vehicle systems\, the statistical modeling of urban systems\, energy and climate issues\, the economic impacts of transport policy\, and crash occurrence and consequences. Her and her students’ work can be found at www.caee.utexas.edu/prof/kockelman. They hope you will join them each year in our world’s carbon-free\, cost-free Bridging Transportation Researchers conference: https://bridgingtransport.org/.
URL:https://c2smart.engineering.nyu.edu/event/seminar-self-driving-vehicles-as-transit-in-us-settings-complementing-buses-and-trains-with-demand-responsive-savs/
CATEGORIES:Seminars,Student Events
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20251016T180000
DTEND;TZID=America/New_York:20251016T190000
DTSTAMP:20260429T082849
CREATED:20251014T190229Z
LAST-MODIFIED:20251016T162246Z
UID:89870-1760637600-1760641200@c2smart.engineering.nyu.edu
SUMMARY:Author Talk: A Conversation with Michael M. Greenburg
DESCRIPTION:This Thursday is the NYU Press Author Talk with Mr. Michael Greenburg. The book focuses on William LeMessurier\, the structural engineer who discovered a fatal flaw in his building’s design and his decision to blow the whistle on himself. Please make sure you register for the event here if you plan to attend. \nFood & refreshments provided.
URL:https://c2smart.engineering.nyu.edu/event/author-talk-a-conversation-with-michael-m-greenburg/
LOCATION:Dibner Library\, 5 MetroTech\, Brooklyn\, NY\, 11201\, United States
CATEGORIES:Conferences,Seminars,Student Events,Webinars
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20251010T080000
DTEND;TZID=America/New_York:20251010T120000
DTSTAMP:20260429T082849
CREATED:20251002T194503Z
LAST-MODIFIED:20251002T194503Z
UID:89836-1760083200-1760097600@c2smart.engineering.nyu.edu
SUMMARY:NYU Tandon and Verizon present: AI and You
DESCRIPTION:Join NYU Tandon and Verizon at an event to learn about AI and how it is involved in your everyday lives.  Speakers include: Emily Black\, Joseph Chow\, Rumi Chunara\, Emilia David\, Ashley Greenspan\, Shri Iyer\, Stacy Matlen\, Shema Mbyirukira\, Maurizio Porfiri!
URL:https://c2smart.engineering.nyu.edu/event/nyu-tandon-and-verizon-present-ai-and-you/
LOCATION:Pfizer Auditorium\, 5 MetroTech\, Brooklyn\, NY\, 11201\, United States
CATEGORIES:Seminars,Student Events
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20250925T080000
DTEND;TZID=America/New_York:20250925T180000
DTSTAMP:20260429T082849
CREATED:20250828T185213Z
LAST-MODIFIED:20250828T185213Z
UID:89201-1758787200-1758823200@c2smart.engineering.nyu.edu
SUMMARY:2025 Sustainable Cities Summit: Day 2
DESCRIPTION:We are proud to support the second annual Sustainable Cities Summit in partnership with Climate Group and NYC Climate Week. This event brings together various experts from multiple organizations to discuss climate-forward cities and mainstream climate action for a sustainable future. \nDiscover how design\, data\, and collaboration are reshaping New York’s future—and inspiring cities around the world. As part of #ClimateWeekNYC\, Sidara companies are joining forces with NYU to host a full-day summit focused on implementable solutions for healthier\, more sustainable urban living. The event feature leading experts from TYLin\, Introba\, Perkins & Will\, and Currie & Brown\, alongside thought leaders from NYU\, MIT\, C40 Cities\, the City of New York\, and the Los Angeles Cleantech Incubator.
URL:https://c2smart.engineering.nyu.edu/event/2025-sustainable-cities-summit-day-2/
LOCATION:Kimmel Center\, Room 914\, 60 Washington Square South\, New York\, NY\, 10012\, United States
CATEGORIES:Seminars,Student Events
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20250912
DTEND;VALUE=DATE:20250913
DTSTAMP:20260429T082849
CREATED:20250805T154439Z
LAST-MODIFIED:20250805T155935Z
UID:89046-1757635200-1757721599@c2smart.engineering.nyu.edu
SUMMARY:New York Reinforcement Learning Workshop (NYRL)
DESCRIPTION:Join leading researchers from academia and industry for the inaugural NYRL Workshop. Connect\, collaborate\, and explore the latest advances in reinforcement learning with the vibrant New York metropolitan RL community. \nCo-organized by Amazon\, Columbia Business School (CBS)\, and NYU Tandon School of Engineering.
URL:https://c2smart.engineering.nyu.edu/event/new-york-reinforcement-learning-workshop-nyrl/
CATEGORIES:Conferences,Seminars,Student Events
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20250910T123000
DTEND;TZID=America/New_York:20250910T133000
DTSTAMP:20260429T082849
CREATED:20250910T154455Z
LAST-MODIFIED:20250910T154455Z
UID:89274-1757507400-1757511000@c2smart.engineering.nyu.edu
SUMMARY:CUE Distinguished Speaker Series: Katus Watson\, Jacobs
DESCRIPTION:
URL:https://c2smart.engineering.nyu.edu/event/cue-distinguished-speaker-series-katus-watson-jacobs/
LOCATION:C2SMART Center Viz Lab\, 6 Metrotech Center\, Room 460\, Brooklyn\, 11201
CATEGORIES:Seminars
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20250708T130000
DTEND;TZID=America/New_York:20250708T140000
DTSTAMP:20260429T082849
CREATED:20250612T172822Z
LAST-MODIFIED:20250701T154452Z
UID:88890-1751979600-1751983200@c2smart.engineering.nyu.edu
SUMMARY:Seminar: Improving the Quality of Urban Public Transport: Lessons Learned from a Novel Use of GPS Data
DESCRIPTION:In Italy\, public transport is typically operated by private companies under service contracts including penalties for non-compliance. Therefore\, detecting anomalous traffic days is key to fairly assigning delay responsibility for buses operating in mixed traffic: operators should not be penalized on days of exceptional traffic conditions. To address this\, harmonic average speeds of vehicles are used to cluster hours of the day exhibiting similar traffic patterns. For any of such traffic states\, a Generalized Additive Model is fit to the available speed percentiles in order to detect anomalous days. A case study relying on GPS data is presented for the city of Trieste.\n\nPresented by Andrea Mecchina\, PhD candidate\, University of Trieste\, Italy
URL:https://c2smart.engineering.nyu.edu/event/save-the-date-seminar-andrea-mecchina-university-of-trieste-italy/
CATEGORIES:Seminars,Student Events
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20250701T123000
DTEND;TZID=America/New_York:20250701T133000
DTSTAMP:20260429T082849
CREATED:20250701T154822Z
LAST-MODIFIED:20250701T154850Z
UID:88960-1751373000-1751376600@c2smart.engineering.nyu.edu
SUMMARY:Summer Programs Welcome Lunch!
DESCRIPTION:
URL:https://c2smart.engineering.nyu.edu/event/summer-programs-welcome-lunch/
LOCATION:C2SMART Center Viz Lab\, 6 Metrotech Center\, Room 460\, Brooklyn\, 11201
CATEGORIES:Seminars,Student Events
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20250507T130000
DTEND;TZID=America/New_York:20250507T140000
DTSTAMP:20260429T082849
CREATED:20250422T173123Z
LAST-MODIFIED:20250506T154823Z
UID:88555-1746622800-1746626400@c2smart.engineering.nyu.edu
SUMMARY:Prof. Vinitsky Seminar: Robust Self-driving Emerges from Self-play
DESCRIPTION:Self-play has powered breakthroughs in two-player and multi-player games. Here we show that self-play is a surprisingly effective strategy in another domain. We show that robust and naturalistic driving emerges entirely from self-play in simulation at unprecedented scale — 1.6~billion~km of driving. This is enabled by Gigaflow\, a batched simulator that can synthesize and train on 42 years of subjective driving experience per hour on a single 8-GPU node. The resulting policy achieves state-of-the-art performance on three independent autonomous driving benchmarks. The policy outperforms the prior state of the art when tested on recorded real-world scenarios\, amidst human drivers\, without ever seeing human data during training. The policy is realistic when assessed against human references and achieves unprecedented robustness\, averaging 17.5 years of continuous driving between incidents in simulation.
URL:https://c2smart.engineering.nyu.edu/event/prof-vinitsky-seminar-robust-self-driving-emerges-from-self-play/
LOCATION:C2SMART Center Viz Lab\, 6 Metrotech Center\, Room 460\, Brooklyn\, 11201
CATEGORIES:Seminars,Webinars
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20250423T140000
DTEND;TZID=America/New_York:20250423T150000
DTSTAMP:20260429T082849
CREATED:20250304T192602Z
LAST-MODIFIED:20250304T192602Z
UID:87966-1745416800-1745420400@c2smart.engineering.nyu.edu
SUMMARY:Fireside Chat with David Hammer\, co-founder of Popwheels
DESCRIPTION:This student-moderated Fireside Chat will feature David Hammer\, co-founder of Popwheels\, a cutting-edge e-bike battery swap network. David will discuss his career trajectory\, the challenges of standing up urban-scale technology in NYC\, and more!
URL:https://c2smart.engineering.nyu.edu/event/fireside-chat-with-david-hammer-co-founder-of-popwheels/
LOCATION:C2SMART Center Viz Lab\, 6 Metrotech Center\, Room 460\, Brooklyn\, 11201
CATEGORIES:Seminars,Student Events
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20250422T173000
DTEND;TZID=America/New_York:20250422T190000
DTSTAMP:20260429T082849
CREATED:20250410T193226Z
LAST-MODIFIED:20250410T193226Z
UID:88432-1745343000-1745348400@c2smart.engineering.nyu.edu
SUMMARY:AI: Forging the Future of the AEC Industry
DESCRIPTION:Artificial intelligence (AI) is revolutionizing the architecture\, engineering\, and construction (AEC) industry by driving innovation across planning\, design\, construction\, and operations. At the core of this transformation is the ability to collect\, process\, and act on vast amounts of data in ways that were previously unimaginable. \nTo explore these groundbreaking developments\, New York University and Professional Women in Construction of New York have assembled a panel of visionary leaders who will assess AI alternatives and discuss how they are shaping the future of the AEC industry. \nThis event will provide an invaluable opportunity to gain insights into how AI is redefining workflows and creating new possibilities for professionals in this field.\n \nEvent Details:\n Date: Tuesday\, April 22\, 2025\n Time:  5:30 PM – 7:00 PM (EDT)\n Location: Pfizer Auditorium\, 5 Metrotech\, Brooklyn\, NY\n \nPanelists:\nSemiha Ergan\, NYU Tandon School of Engineering\, Civil and Urban Engineering Department \nKiSeok Jeon\, STV\nMelissa Forstell McAneny. Trunk Tools\nMonica Nelson\, Gilbane Building Company\n\n \nModerator:\nMohamad Awada\, NYU Tandon School of Engineering\,Civil and Urban Engineering Department 
URL:https://c2smart.engineering.nyu.edu/event/ai-forging-the-future-of-the-aec-industry/
LOCATION:5 metro\, 5 MetroTech\, Brooklyn\, NY\, 11201\, United States
CATEGORIES:Seminars
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20250416T130000
DTEND;TZID=America/New_York:20250416T140000
DTSTAMP:20260429T082849
CREATED:20250402T154334Z
LAST-MODIFIED:20250402T154334Z
UID:88242-1744808400-1744812000@c2smart.engineering.nyu.edu
SUMMARY:Seminar: Investigating Vulnerabilities in Autonomous Vehicle Perception Algorithms
DESCRIPTION:Autonomous vehicles (AVs) rely on deep neural networks (DNNs) for critical tasks such as environment perception—identifying traffic signs\, pedestrians\, and lane markings—and executing control decisions like braking\, acceleration\, and lane changing. However\, DNNs are vulnerable to adversarial attacks\, including structured perturbations to inputs and misleading training samples that can degrade performance. This presentation begins with an overview of adversarial training\, emphasizing the impact of input sizes on DNNs’ vulnerability to cyberattacks. Subsequently\, I will share our recent findings that explore the hypothesis that DNNs learn piecewise linear relationships between inputs and outputs. This conjecture is crucial for developing both adversarial attacks and defense strategies in machine learning security. The last part of the presentation will focus on recent work on using error-correcting codes to safeguard DNN-based classifiers. \nDr. Saif Jabari is an Associate Professor of Civil and Urban Engineering at New York University Abu Dhabi (NYUAD) and a Global Network Associate Professor at the Tandon School of Engineering at NYU in Brooklyn\, NY. At NYUAD\, he is co-PI of the Center for Integrated Urban Networks (CITIES) and the Center for Stability\, Instability\, and Turbulence (SITE). He is an Associate Editor for Transportation Science and Area Editor with the new Elsevier journal Artificial Intelligence for Transportation. His research focuses on developing advanced computational methods and theoretical guarantees of performance for urban traffic management problems. The techniques integrate traffic data\, typically in high resolution\, with principles of traffic physics to address the rapidly evolving needs of the field. His current research focuses on understanding and addressing vulnerabilities in deep neural networks\, specifically as they relate to environment perception in autonomous vehicles.
URL:https://c2smart.engineering.nyu.edu/event/seminar-investigating-vulnerabilities-in-autonomous-vehicle-perception-algorithms/
LOCATION:C2SMART Center Viz Lab\, 6 Metrotech Center\, Room 460\, Brooklyn\, 11201
CATEGORIES:Seminars
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20250411T093000
DTEND;TZID=America/New_York:20250411T103000
DTSTAMP:20260429T082849
CREATED:20250407T164354Z
LAST-MODIFIED:20250407T180200Z
UID:88400-1744363800-1744367400@c2smart.engineering.nyu.edu
SUMMARY:Seminar: Spatiotemporal Drought Analysis and Prediction: From Pattern Tracking to Impact Assessment
DESCRIPTION:The increasing frequency and severity of drought events worldwide demand innovative approaches that can effectively characterize\, track\, predict\, and assess impacts of the complex spatiotemporal dynamics of water scarcity. This presentation explores how integrated spatiotemporal methodologies enhance drought monitoring\, forecasting\, and impact assessment across diverse global regions. \nOur research demonstrates a logical progression from fundamental spatiotemporal drought tracking to advanced prediction methodologies and practical impact assessment. Beginning with approaches to construct drought tracks through space and time in India\, we identify key drought characteristics including onset location\, pathway\, duration\, severity\, and rotation. These spatial patterns reveal critical information about drought migration and evolution that provide insights into underlying climate and land surface drivers. \nBuilding on this foundation of spatiotemporal drought characterization\, we apply machine learning techniques to predict drought occurrence and intensity across Kazakhstan’s diverse climate zones. By utilizing non-contiguous drought analysis for feature extraction\, machine learning models achieve remarkable prediction accuracy at lead times of up to six months in these arid and semi-arid regions. Additionally\, deep learning techniques enhanced with ensemble empirical mode decomposition substantially improve soil moisture anomaly forecasting in China’s Huai River basin by better capturing the complex non-stationary time series characteristics of drought evolution. \nBeyond monitoring and forecasting\, we extend our approach to predict drought impacts on agriculture in Northeast India using spatiotemporal drought patterns as input for crop yield forecasting. This methodology integrates polynomial regression and artificial neural network models\, where the spatial extent and temporal evolution of drought areas serve as key predictive features. The results demonstrate that changes in drought area and its temporal aggregation provide an important pre-processing alternative for implementing machine learning models for drought impact prediction. \nThese integrated approaches\, spanning regions from Central Asia to South and East Asia\, contribute to a more robust understanding of drought dynamics by revealing how drought moves and evolves in space and time\, enabling more effective early warning systems and supporting agricultural decision-making in increasingly water-stressed environments. Across all applications and geographical contexts\, the spatiotemporal properties of drought emerge as key features that significantly enhance the performance of machine learning prediction models. \nBio: Dr. Gerald A. Corzo is an Associate Professor of Hydroinformatics at IHE Delft Institute for Water Education\, where he leads cutting-edge research that uses Artificial Intelligence and Machine Learning to address critical challenges in climate adaptation and water resource management. His research on hydrometeorological extremes has helped us better understand\, predict\, and respond to floods and droughts across the globe. As Principal Investigator on significant EU-funded projects like EU-WATCH\, Climate Intelligent (EU-CLINT) and EU-NAIADES\, Dr. Corzo has developed cutting-edge AI-driven tools that enhance decision-making in water management and climate resilience. He currently serves as an Editor of the Journal of Hydrology (Elsevier) and was recognized with the prestigious IAHS Tison Award for his contributions to hydrological sciences in 2012. Dr. Corzo’s interdisciplinary approach integrates environmental science with advanced computational technologies to create practical solutions aligned with sustainable development goals\, particularly for enhancing ecosystem resilience in vulnerable communities worldwide.
URL:https://c2smart.engineering.nyu.edu/event/seminar-spatiotemporal-drought-analysis-and-prediction-from-pattern-tracking-to-impact-assessment/
LOCATION:C2SMART Center Viz Lab\, 6 Metrotech Center\, Room 460\, Brooklyn\, 11201
CATEGORIES:Seminars
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20250312T180000
DTEND;TZID=America/New_York:20250312T190000
DTSTAMP:20260429T082850
CREATED:20250304T190125Z
LAST-MODIFIED:20250304T190352Z
UID:87951-1741802400-1741806000@c2smart.engineering.nyu.edu
SUMMARY:2025 Women in Transportation Panel & Networking
DESCRIPTION: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 DOT & Adjunct Lecturer at Hunter College. The discussion will be moderated by NYU PhD Candidate Zerun Liu.\n\n\nLight refreshments will be provided! Register for the Zoom here.
URL:https://c2smart.engineering.nyu.edu/event/2025-women-in-transportation-panel-networking/
LOCATION:C2SMART Center Viz Lab\, 6 Metrotech Center\, Room 460\, Brooklyn\, 11201
CATEGORIES:Seminars,Student Events
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20250218T140000
DTEND;TZID=America/New_York:20250218T150000
DTSTAMP:20260429T082850
CREATED:20250116T203640Z
LAST-MODIFIED:20250218T163925Z
UID:87727-1739887200-1739890800@c2smart.engineering.nyu.edu
SUMMARY:Seminar: Gittins Indices for Cost-aware and Freeze-thaw Bayesian Optimization
DESCRIPTION:Presented by Qian Xie\, Cornell \nHyperparameter optimization is crucial in real-world applications such as machine learning model training\, robotics control\, material design\, and plasma physics. In transportation\, hyperparameter optimization plays a significant role in applications like traffic flow prediction\, dynamic pricing\, route planning\, and public transportation scheduling\, where complex models need to be fine-tuned to achieve optimal performance. These scenarios are often modeled as black-box functions\, which take hyperparameters as inputs and output performance metrics. Bayesian optimization is a powerful framework for efficiently optimizing such black-box functions\, especially when evaluations are time-consuming or expensive. However\, practical factors such as varying function evaluation costs and observable partial feedback during function evaluation remain under-explored in this framework. My research leverages Gittins indices\, which are inherently cost-aware and feedback-aware\, by drawing connections to Pandora’s Box problems and Markovian/Bayesian bandits\, where Gittins indices are Bayesian optimal. \nIn the first half of my talk\, I will present my published work\, which adapts Gittins indices into a cost-aware acquisition function class for Bayesian optimization\, demonstrating competitive empirical performance\, particularly in medium-to-high dimensions. In the second half\, I will discuss my ongoing work on developing Gittins indices for freeze-thaw Bayesian optimization involving decisions on early stopping and switching of hyperparameter tests based on partial feedback.
URL:https://c2smart.engineering.nyu.edu/event/seminar-gittins-indices-for-cost-aware-and-freeze-thaw-bayesian-optimization/
LOCATION:C2SMART Center Viz Lab\, 6 Metrotech Center\, Room 460\, Brooklyn\, 11201
CATEGORIES:Seminars,Virtual Events,Webinars
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20250110T150000
DTEND;TZID=America/New_York:20250110T173000
DTSTAMP:20260429T082850
CREATED:20241209T193758Z
LAST-MODIFIED:20250522T160008Z
UID:87354-1736521200-1736530200@c2smart.engineering.nyu.edu
SUMMARY:Seminar: Klaus Bogenberger/C2SMARTER Research Exchange
DESCRIPTION:The MobilityCoin is a new currency for paying for all your daily trips within a metropolitan area. At the beginning of each year\, the MobilityCoin Agency allocates a specific number of coins to each person. The price of a trip depends on the mode\, traffic state\, occupancy\, and trip length or dura@on. If you make a trip with a vehicle or public transport you pay a dynamic price with MobilityCoins. The use of environmentally friendly modes like biking or walking is incentivized by earning MobilityCoins. All users are allowed to buy and sell MobilityCoins in the MobilityCoin Market\, which is regulated by the MobilityCoin Agency. It controls the market volume and price limits\, it limits the number of coins a person can buy or sell and defines a transaction fee. The MobilityCoin system is an all-in-one approach\, uniting different traffic management measures – it simultaneously optimizes supply and demand of the transportation system to accomplish environmental\, social\, and economic objectives\, e.g.\, emission reduction\, livability of urban space\, public participation\, and infrastructure funding. The system influences infrastructure supply\, mobility tool ownership\, and mode choice. It is open to all types of technology\, enables the fair financing of new infrastructure\, and provides an adjustable\, market-based and reliable pricing mechanism for mobility in limited urban space. The MobilityCoin system creates a transparent decision-making process and gradually re-allocates mobility space by enabling public participation. It also accounts for social acceptance and fairness by allocating a mobility budget to each person according to their mobility needs rather than their income or wealth.
URL:https://c2smart.engineering.nyu.edu/event/seminar-klaus-bogenberger-c2smarter-research-exchange/
CATEGORIES:Seminars
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20250110T080000
DTEND;TZID=America/New_York:20250110T170000
DTSTAMP:20260429T082850
CREATED:20241219T194755Z
LAST-MODIFIED:20241219T202057Z
UID:87509-1736496000-1736528400@c2smart.engineering.nyu.edu
SUMMARY:8th NYUAD Transportation Symposium
DESCRIPTION:The main theme of the 8th NYUAD Transportation Symposium is Transportation and AI: Opportunities and Challenges. Artificial Intelligence (AI) has the potential to revolutionize the transportation industry\, by increasing efficiency and accessibility\, but it also presents several challenges that need to be addressed\, including safety and ethical constraints. The 8th NYUAD Transportation Symposium\, held at 19 Washington Square in New York City\, will be a forum for the exchange of ideas among scholars who are active in these areas of research.
URL:https://c2smart.engineering.nyu.edu/event/8th-nyuad-transportation-symposium/
LOCATION:19 Washington Square North\, 19 Washington Square North\, NY\, NY
CATEGORIES:Seminars
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20241210T123000
DTEND;TZID=America/New_York:20241210T133000
DTSTAMP:20260429T082850
CREATED:20241202T195938Z
LAST-MODIFIED:20241203T175118Z
UID:87203-1733833800-1733837400@c2smart.engineering.nyu.edu
SUMMARY:Seminar: Positive Feedback in Transportation Systems
DESCRIPTION:This talk will present tractable models of road traffic and transit which feature positive feedback\, whereby my travel choice (e.g.\, whether to travel\, what mode to take\, etc.) leads others to make the same choice. Positive feedback amplifies policy impacts and can lead surprising results\, such as a toll that raises traffic demand and a road expansion that cuts it. Overall\, the talk will demonstrate the insights possible from incorporating economic thinking into detailed engineering models. I will also show my group’s AI chatbot that answers questions about transit systems. \nSince 2018\, Lewis Lehe has been an assistant professor in the transportation systems group at the Department of Civil and Environmental Engineering\, University of Illinois Urbana-Champaign. His research focuses on the economics and measurement of travel in cities. He holds an MA in Transport Economics of University of Leeds\, and MS and PhD degrees in civil engineering from UC Berkeley. He serves on TRB’s Economics and Finance Committee\, as the Treasurer of Findings Press and as Communications Officer of the International Transportation Economics Association.
URL:https://c2smart.engineering.nyu.edu/event/positive-feedback-in-transportation-systems/
LOCATION:C2SMART Center Viz Lab\, 6 Metrotech Center\, Room 460\, Brooklyn\, 11201
CATEGORIES:Seminars
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20241119T113000
DTEND;TZID=America/New_York:20241119T123000
DTSTAMP:20260429T082850
CREATED:20240808T153418Z
LAST-MODIFIED:20241031T153745Z
UID:85880-1732015800-1732019400@c2smart.engineering.nyu.edu
SUMMARY:Distinguished Speaker Series: Dr. Henry Liu
DESCRIPTION:Earning public trust in highly automated vehicles\, and greater understanding of how they operate\, is paramount as automakers and their suppliers push to put cars and trucks on the road that can safely operate without a driver. While complex automated vehicle safety testing programs are being implemented across industry\, they are generally proprietary\, and their structure remains hidden from public view. To fill in this gap\, we developed the Mcity Safety Assessment Program\, a two-part protocol for testing the behavior competence of automated vehicles before their widespread use on public roads. The first part of the assessment is a “Driver’s License Test” that measures the basic behavioral competency of an automated vehicle through random scenario generation. The second part is a “Driving Intelligence Test” that challenges AI-based algorithms with a diverse set of scenarios representing those that most often result in crashes\, injuries and fatalities. Mcity believes the Mcity Safety Assessment Program could serve as the blueprint for a publicly inspectable behavioral safety framework\, helping industry bring automated vehicle technology to market in a manner that truly benefits society. In this talk\, we will also highlight Mcity 2.0\, a facility funded by the National Science Foundation\, that aims to build a digital infrastructure providing researchers remote access to the Mcity mixed reality testing environment for highly automated vehicles.
URL:https://c2smart.engineering.nyu.edu/event/distinguished-speaker-series-dr-henry-liu/
LOCATION:C2SMART Center Viz Lab\, 6 Metrotech Center\, Room 460\, Brooklyn\, 11201
CATEGORIES:Seminars
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20241114T190000
DTEND;TZID=America/New_York:20241114T210000
DTSTAMP:20260429T082850
CREATED:20241111T224304Z
LAST-MODIFIED:20241111T224408Z
UID:86450-1731610800-1731618000@c2smart.engineering.nyu.edu
SUMMARY:NYU SPS Distinguished Speaker Series: Nicholas Lalla
DESCRIPTION:Nicholas Lalla is an urbanist\, executive leader\, and author working at the intersection of economic development and emerging technology. He partners with cities to build strategies and initiatives that catalyze inclusive growth. Lalla founded Tulsa Innovation Labs\, an organization deploying more than $200 million to build northeast Oklahoma’s innovation economy. He previously led Cyber NYC for the New York City Economic Development Corporation\, a cybersecurity initiative the New York Times called “among the nation’s most ambitious.” Earlier in his career\, at the Urban Land Institute\, he launched a national resilience program for cities\ncombatting the effects of climate change. Lalla has written for Newsweek\, Fast Company\, Stanford Social Innovation Review\, and Next City\, among other outlets. His book Reinventing the Heartland is forthcoming from HarperCollins. He can be found online at nicholaslalla.com.
URL:https://c2smart.engineering.nyu.edu/event/nyu-sps-distinguished-speaker-series-nicholas-lalla/
CATEGORIES:Seminars
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20241107T141500
DTEND;TZID=America/New_York:20241107T151500
DTSTAMP:20260429T082850
CREATED:20240808T153239Z
LAST-MODIFIED:20241106T195604Z
UID:85877-1730988900-1730992500@c2smart.engineering.nyu.edu
SUMMARY:Seminar: Alternative Fuel Vehicle Evacuation and Refueling Infrastructure Location Planning
DESCRIPTION:Abstract: Climate change exacerbates the frequency and impacts of hazardous events\, such as hurricanes\, flooding\, and wildfires. During emergencies that require preemptive evacuation\, drivers using alternative fuel vehicles can be vulnerable under conventional evacuation routes that do not provide access to refueling and charging stations on their way to safety. In this talk\, I will discuss a novel evacuation routing problem considering multiple fuel vehicle types. An evacuation tree problem with hop constraints that capture each vehicle fuel type & refueling/charging needs as they are routed to safety is introduced. Large-scale network numerical experiments in South Florida are conducted and planning insights are presented. Even though refueling and charging infrastructure is deployed to meet habitual travel demand\, in the second part of my talk I will focus on the extension of the alt-fuel evacuation problem to decide the location of emergency refueling and/or charging infrastructure on the transportation network. \nBio: Dr. Kontou is an assistant professor in the Department of Civil and Environmental Engineering at the University of Illinois Urbana-Champaign. Her research focuses on planning sustainable transportation systems. She earned her Ph.D. in Civil Engineering\, focusing on transportation systems\, from University of Florida\, and holds a M.Sc. from Virginia Tech\, and a Diploma from the National Technical University of Athens in the same field. She was a postdoctoral research associate at the National Renewable Energy Lab and the Department of City and Regional Planning at the University of North Carolina at Chapel Hill. Dr. Kontou is a 2023 NSF CAREER awardee\, a 2023 CUTC-Cambridge Systematics New Faculty Award recipient\, a 2022 Illinois-Indiana Sea Grant Faculty Scholar\, a 2021 US Frontiers of Engineering Invited Participant\, and a Levenick Sustainability Teaching Fellow at the University of Illinois. She is a member of the Transportation Research Board Committee on Alternative Transportation Fuels and Technologies and an Associate Editor of the Transportation Research Part D: Transport and Environment journal.
URL:https://c2smart.engineering.nyu.edu/event/seminar-ria-kontou/
LOCATION:C2SMART Center Viz Lab\, 6 Metrotech Center\, Room 460\, Brooklyn\, 11201
CATEGORIES:Seminars
END:VEVENT
END:VCALENDAR