AI & Deep Learning
Sub brand
Back to top


Date: Thursday, October 27, 2022
Time: 9:00am - 11:00am PT
Duration: 2 hour

Join this webinar to meet NVIDIA FLARE, an open-source platform for federated learning. With tools for building applications and deploying and managing federated learning workflows, FLARE lets researchers and data scientists adapt their machine learning and deep learning workflows to a federated paradigm.

Together, we’ll explore the architecture, key concepts, components, and capabilities of the platform. We’ll also check out the built-in algorithms for federated training and evaluation with privacy preservation and highlight the tools that help developers come up to speed quickly. Finally, we’ll take a look at what it takes to go from a proof-of-concept simulation to real-world deployment.

Join this webinar to learn about:
  • Federated data science workflows
  • The state of federated learning research with NVIDIA FLARE
  • What’s new in v2.2, the latest release

Join us after the presentation for a live Q&A session.

    Webinar Registration


    You will receive an email with instructions on how to join the webinar shortly.


    Content goes here


    content goes here

    main image description


    Content goes here


    DGX Station Datasheet

    Get a quick low-down and technical specs for the DGX Station.
    DGX Station Whitepaper

    Dive deeper into the DGX Station and learn more about the architecture, NVLink, frameworks, tools and more.
    DGX Station Whitepaper

    Dive deeper into the DGX Station and learn more about the architecture, NVLink, frameworks, tools and more.


    Content goes here


    Kris Kersten

    Technical Marketing Engineer

    Kris is a technical marketing engineer at NVIDIA who's focused on AI and distributed computing, working to scale machine learning and deep learning solutions to solve today's most pressing problems in healthcare. Prior to NVIDIA, Kris worked at Cray Supercomputers, studying hardware and software performance characteristics from low-level cache benchmarking to large-scale parallel simulation.

    Chester Chen

    Senior Manager, Federated Learning, NVIDIA

    Chester is a senior manager on the federated learning engineering team at NVIDIA. He has over 20 years of experience in building and managing different types of systems and operations. Before NVIDIA, he spent six years as the director of data science engineering at GoPro, where he was in charge of GoPro's data lake infrastructure, data engineering, data analytics, and machine learning applications. Prior to GoPro, he played many different roles, including director of engineering, technical director, and system architect, at many different big companies and small startups in Silicon Valley.

    Holger Roth

    Principal Applied Research Scientist

    Holger is a principal applied research scientist at NVIDIA, focusing on deep learning for medical imaging. He's been working closely with clinicians and academics over the past several years to develop deep learning-based medical image computing and computer-aided detection models for radiological applications. He's an associate editor for IEEE Transactions of Medical Imaging and holds a PhD from University College London, UK. In 2018, he was awarded the MICCAI Young Scientist Publication Impact Award.

    Presenter 4 Name

    Job Title 4

    Presenter 4 Bio

    Other Speakers


    Job Title.
    Name 2

    Job Title.
    Name 3

    Job Title.

    Content Title

    Content here


    Webinar: Description here

    Date & Time: Wednesday, April 22, 2018