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X-ORIGINAL-URL:https://c2smart.engineering.nyu.edu
X-WR-CALDESC:Events for C2SMART Home
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DTSTART;TZID=America/New_York:20251107T120000
DTEND;TZID=America/New_York:20251107T130000
DTSTAMP:20260422T181831
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LAST-MODIFIED:20251016T154452Z
UID:89896-1762516800-1762520400@c2smart.engineering.nyu.edu
SUMMARY:Student Learning Hub: Introduction to Online Recommendation Systems: From Predict-Sort Architecture to Real-Time Feature Service
DESCRIPTION:This session introduces how modern online recommendation systems\, like TikTok shop\, deliver personalized content in real time. I’ll walk through the overall system architecture and then focus on the predict-sort stage\, explaining how BFS (Bytedance Feature Service) and UDA (User Data Accessor) enable large-scale feature computation using a DAG-based (Directed Acyclic Graph) operator framework and a domain-specific language (DSL). Participants will gain insight into how these components work together to achieve millisecond-level predictions. Hosted by NYU’s Hongdao Meng!
URL:https://c2smart.engineering.nyu.edu/event/student-learning-hub-introduction-to-online-recommendation-systems-from-predict-sort-architecture-to-real-time-feature-service/
CATEGORIES:Student Events,Webinars
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20251112T130000
DTEND;TZID=America/New_York:20251112T140000
DTSTAMP:20260422T181831
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
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BEGIN:VEVENT
DTSTART;TZID=America/New_York:20251121T120000
DTEND;TZID=America/New_York:20251121T130000
DTSTAMP:20260422T181831
CREATED:20251016T154633Z
LAST-MODIFIED:20251016T154633Z
UID:89901-1763726400-1763730000@c2smart.engineering.nyu.edu
SUMMARY:Student Learning Hub: Building a Scalable Multithreaded Processing System on AWS Cloud
DESCRIPTION:This lecture introduces the design and implementation of a serverless multithreaded processing system using AWS Step Functions\, AWS Lambda\, and Amazon S3. The session covers how to orchestrate parallel tasks\, manage state transitions\, and scale processing pipelines efficiently on the AWS cloud platform. Emphasis will be placed on cloud-native scalability\, fault tolerance\, and cost optimization through automation and serverless architecture. Hosted by NYU’s Zhi Jie (Jeffrey) Wang!
URL:https://c2smart.engineering.nyu.edu/event/student-learning-hub-building-a-scalable-multithreaded-processing-system-on-aws-cloud/
CATEGORIES:Student Events,Webinars
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BEGIN:VEVENT
DTSTART;TZID=America/New_York:20260311T120000
DTEND;TZID=America/New_York:20260311T130000
DTSTAMP:20260422T181831
CREATED:20260304T145623Z
LAST-MODIFIED:20260304T145623Z
UID:90556-1773230400-1773234000@c2smart.engineering.nyu.edu
SUMMARY:Webinar: AI Agent 101 and Vibe Coding Demo
DESCRIPTION:This talk introduces the core concepts behind modern AI agents—from (Large Language Models) LLMs and memory to tool integration\, reusable agent skills\, and autonomous workflows. Participants will gain a clear understanding of how prompting\, function calling\, and multi-agent coordination work in practice. The webinar will include a live “vibe coding” demo to prototype use cases such as a transportation data dashboard using Google AI Studio\, VS Code + AI extensions\, and Claude Desktop to demonstrate how AI agents can orchestrate tools and skills to accelerate development\, automate data workflows\, and support transportation analytics and decision-making. \nPresented by Dr. Yu Hu\, Senior Software Engineer at Comcast.
URL:https://c2smart.engineering.nyu.edu/event/webinar-ai-agent-101-and-vibe-coding-demo/
CATEGORIES:Student Events,Webinars
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DTSTART;TZID=America/New_York:20260313T150000
DTEND;TZID=America/New_York:20260313T160000
DTSTAMP:20260422T181831
CREATED:20260309T151845Z
LAST-MODIFIED:20260309T152634Z
UID:90578-1773414000-1773417600@c2smart.engineering.nyu.edu
SUMMARY:MTA x NYU: Demystifying the Application Process
DESCRIPTION:Kawanza Williams serves as Senior Manager of Emerging Talent at the Metropolitan Transportation Authority (MTA)\, where she leads initiatives focused on talent development\, retention\, and strategic workforce partnerships. In her role as Employee Manager of Retention & External Partnerships\, she oversees the full lifecycle of the MTA’s internship programs\, guiding interns from onboarding through professional development and\, when applicable\, transition into permanent roles. Kawanza works closely with senior leadership\, external partners\, and vendors to ensure that talent pipelines align with organizational priorities and operational needs. Her leadership emphasizes structured career pathways\, sustainable workforce development\, and cost-conscious program design that supports long-term institutional growth. Through her work\, she plays a central role in shaping how emerging professionals enter\, navigate\, and advance within one of the largest public transportation systems in North America.
URL:https://c2smart.engineering.nyu.edu/event/mta-x-nyu-demystifying-the-application-process/
CATEGORIES:Student Events,Webinars
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BEGIN:VEVENT
DTSTART;TZID=America/New_York:20260327T123000
DTEND;TZID=America/New_York:20260327T133000
DTSTAMP:20260422T181831
CREATED:20260304T152522Z
LAST-MODIFIED:20260304T152522Z
UID:90559-1774614600-1774618200@c2smart.engineering.nyu.edu
SUMMARY:SLH: Introduction to Bayesian Optimization and Its Applications in Transportation and AI
DESCRIPTION:This talk introduces Bayesian Optimization (BO)\, a sample-efficient framework for optimizing expensive\, noisy black-box functions. We will cover the core ideas behind surrogate modeling (e.g.\, Gaussian processes) and acquisition functions (such as EI and UCB) that balance exploration and exploitation to find high-performing solutions with limited evaluations. The applications focus on two representative directions: (1) parameter calibration for transportation simulation—tuning behavioral and network parameters so simulated traffic patterns match real observations; and (2) hyperparameter optimization in machine learning—automatically selecting model and training settings to improve accuracy\, robustness\, and efficiency. We will also highlight practical considerations such as constraints\, multi-objective trade-offs\, and scalable implementations.\n\nPresented by NYU’s Yu Tang
URL:https://c2smart.engineering.nyu.edu/event/slh-introduction-to-bayesian-optimization-and-its-applications-in-transportation-and-ai/
CATEGORIES:Student Events,Webinars
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BEGIN:VEVENT
DTSTART;TZID=America/New_York:20260501T110000
DTEND;TZID=America/New_York:20260501T120000
DTSTAMP:20260422T181831
CREATED:20260407T153044Z
LAST-MODIFIED:20260415T171316Z
UID:90727-1777633200-1777636800@c2smart.engineering.nyu.edu
SUMMARY:Bridge Resource Program Rime Webinar: Extending the Service Life of New Jersey Bridge Decks with Internally Cured High Performance Concrete:  Development\, Field Implementation\, and Life Cycle Cost Impacts
DESCRIPTION:Internally cured high performance concrete is a promising strategy for extending the service life of bridge decks in New Jersey. By replacing a portion of normal weight sand with prewetted lightweight fine aggregate\, internal curing provides moisture during hydration\, reducing self desiccation\, early age shrinkage\, and microcracking. These improvements can enhance durability and reduce long term maintenance demands. \nThis work combines complementary efforts on material development and economic evaluation. Rutgers\, in coordination with NJDOT under the Federal Highway Administration EPIC2 initiative\, led the development and assessment of internally cured concrete mixtures through laboratory testing and field implementation. The NYU C2SMART Center\, in collaboration with Rutgers and NJDOT\, evaluated the long term economic implications using life cycle cost analysis. \nSince key inputs such as material premiums\, maintenance timing\, and service life remain uncertain\, the cost evaluation used a stochastic framework informed by NJDOT feedback rather than a purely deterministic approach. Preliminary results indicate that\, despite a modest increase in initial cost\, internally cured high performance concrete can reduce agency costs by up to 40% and total costs by up to 45%. These findings support internal curing as a practical and cost effective approach for more durable bridge decks in New Jersey. \nPresented by NYU’s Eren Kaval and Rutgers’ Michael Ruszala
URL:https://c2smart.engineering.nyu.edu/event/bridge-resource-program-rime-webinar-extending-the-service-life-of-new-jersey-bridge-decks-with-internally-cured-high-performance-concrete-development-field-implementation-and-life-cycle-cost-imp/
CATEGORIES:Student Events,Webinars
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20260525T140000
DTEND;TZID=America/New_York:20260525T150000
DTSTAMP:20260422T181831
CREATED:20260407T152720Z
LAST-MODIFIED:20260416T150511Z
UID:90723-1779717600-1779721200@c2smart.engineering.nyu.edu
SUMMARY:Bridge Resource Program Rime Webinar: Additive Manufacturing Techniques in Infrastructure Applications
DESCRIPTION:Implementation of Additive Construction has increased rapidly across the world. However\, its application still limited in infrastructure projects. The presentation offers a transformative approach to sustainable and structurally efficient construction practices by integrating additive construction (3D printing in construction) with topology optimization\, innovative reinforcement strategies\, and the use of locally sourced raw materials to develop in-house printable concrete mixtures suitable for both in-air and underwater additive construction of structures that meet printability requirements for topology optimization. The presentation will cover three on-going projects at Additive and Robotic Construction Laboratory at Rowan University. \nPresented by Prof. Islam Mantawy\, Assistant Professor in the Department of Civil and Environmental Engineering at Henry M. Rowan College of Engineering\, Rowan University
URL:https://c2smart.engineering.nyu.edu/event/bride-resource-program-rime-webinar-additive-manufacturing-techniques-in-infrastructure-applications/
CATEGORIES:Student Events,Webinars
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