Author Talk: A Conversation with Michael M. Greenburg
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
7 events found.
Webinars
Events
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Dibner Library 5 MetroTech, Brooklyn, NY, United States
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Student Learning Hub: Introduction to Online Recommendation Systems: From Predict-Sort Architecture to Real-Time Feature Service
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
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Seminar: Inverse Learning and Intervention of Transportation Network Equilibrium
C2SMART Center Viz Lab 6 Metrotech Center, Room 460, BrooklynAbstract: By 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
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Student Learning Hub: Building a Scalable Multithreaded Processing System on AWS Cloud
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,
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Webinar: AI Agent 101 and Vibe Coding Demo
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
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MTA x NYU: Demystifying the Application Process
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
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SLH: Introduction to Bayesian Optimization and Its Applications in Transportation and AI
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