Explore featured sessions for HPC, robotics, and data science tools for educational institutions.

Higher education institutions are enabling the workforce of tomorrow, powering next-gen breakthroughs, and driving research that will change lives for generations to come. At GTC, get the tools and resources that will enable you to do your life’s work and solve real-world problems with artificial intelligence.

Featured Speakers

Maurizio Davini
Angela Dai

3D Perception for Semantic Scene Understanding

Angela Dai
Professor, Technical University of Munich

George Karniadakis

Physics-Informed Learning: Recent Developments in PINNs and DeepOnets

George Karniadakis
Professor of Applied Mathematics and Engineering, Brown University

Christoph Studer

Sessions By Topics


  • NVIDIA SimNet: A Neural Engine for Science and Engineering Problems

    • Sanjay Choudhry, Senior Director, NVIDIA

    NVIDIA SimNet is an AI-based solver for engineering and scientific computing problems governed by ordinary and partial differential equations. Students, researchers, and engineers in both academia and industry who are looking to learn about or adopt a neural framework for AI-driven scientific simulations will find this session useful.

  • Physics-Informed Neural Networks for Wave Propagation Using NVIDIA SimNet

    • Harpreet Sethi, Ph.D. Student, Colorado School of Mines

    With the growing availability of big data and compute resources, deep learning in the form of deep neural networks (NNs) has been used in diverse scientific applications. These NNs typically rely entirely on their training data and therefore perform poorly outside of those boundaries. Learn about the accuracy and performance of PINNs using NVIDIA SimNet.

  • Physics Simulation and Deep Reinforcement Learning for Contact-Rich Robotic Assembly

    • Kier Storey, Distinguished Engineer, NVIDIA
    • Yashraj Narang, Senior Research Scientist, NVIDIA

    This session will demonstrate that the latest advances in PhysX 5 within Omniverse allow highly robust, performant, and parallelizable simulations of contact-rich interactions, shown on robotic assembly tasks. We’ll also show that the simulations can be used to collect human demonstrations of such tasks, as well as robots learning to perform the tasks.

  • Early Science Results on the NERSC Perlmutter NVIDIA 100-Powered HPC System

    • Jack Deslippe, Application Performance Group Lead, NERSC, Lawrence Berkeley National Laboratory

    In this session, we’ll discuss the process of preparing applications for the Perlmutter system and early science and chemistry achievements from areas including astrophysics, biology, climate modeling, materials science and chemistry, high-energy physics, fusion science, geosciences, combustion, and other energy science domains.


  • From Fish Facial Recognition to Self-Driving Seeders: Discover how Edge Computing is Modernizing Agriculture

    • Pierre-Antoine Beaudoin, Inception Partner Manager, NVIDIA
    • Ori Shalev, Software Engineering Manager, Arugga
    • Rob Strey, CTO & Cofounder, Plantix
    • Barry Nagel, CTO, UP42
    • George Varvarelis, Cofounder, Novo Senso
    • Julien Cornouiller, Cofounder, Novo Senso

    With an ever-growing population, climate change, and changes in consumer demand, agriculture faces challenges like no other industry. Discover how AI and revolutionary techniques will help not only change the way we produce food, but also cope with the dramatic changes our world is facing.

  • Learning Sim-to-Real Locomotion and Navigation Using NVIDIA's Omniverse

    • David Hoeller, Deep Learning R&D Engineer, NVIDIA

    In this session, you’ll learn how we rely on NVIDIA’s Omniverse ecosystem at the Robotic Systems Lab at ETH Zurich to carry out research in robotics. You’ll discover our quadrupedal robot ANYmal and its extension with an arm called Alma, as well how we learn the complex behaviors for these systems in minutes using reinforcement learning.

  • Level 2 Autonomy for Robotics

    • Zhen Ling Tsai, Senior Machine Learning Engineer, D. Construct

    D.Construct will show a vision RGB-based end-to-end robotics system that takes in high-level suggestions from users to navigate diverse unseen environments autonomously. Learn from the team's experience developing autonomous mobile robots, stress testing, and exploring limitations of such a system, using NVIDIA CUDA, TensorRT, and Jetson Xavier.

  • Open-Source Robotics at 20

    • Brian Gerkey, CEO/Cofounder, Open Robotics

    Through the lens of our work on ROS, you’ll learn about Open Robotics’ recent achievements, current challenges, and future plans. I'll discuss the impact of our efforts, offer insights into our product roadmaps, and argue why you should build your next product on robust open infrastructure.

Data Science

  • Accelerating Data Science: What's New in RAPIDS

    • John Zedlewski, Director of RAPIDS Team, NVIDIA

    This session will start with an overview of the RAPIDS ecosystem, which now includes more than a half-dozen libraries and a wide range of integrations. We'll then dive into some of the recent frontiers of RAPIDS and upcoming features, including improvements to inference, Pandas compatibility, SQL support, and graph analytics.

  • Deep Learning Demystified

    • Ozzy Johnson, Director of Solutions Architecture, NVIDIA

    AI has evolved and improved methods for data analysis and complex computations, solving problems that seemed well beyond our reach only a few years ago. Learn the fundamentals of accelerated data analytics, high-level use cases, and problem-solving methods—as well as how deep learning is transforming every industry.

  • Building a More Diverse and Inclusive Dataset

    • Aaron Carter-Ényì, Director, Africana Digital Ethnography Project
    • Louis Stewart, Head of Strategic Initiatives/Developer Ecosystem, NVIDIA

    Join Louis Stewart, Head of Strategic Initiatives for NVIDIA's developer Ecosystem, along with Dr. Aaron Carter-Enyi (Morehouse University), Laura McPherson (Dartmouth College), and others as we discuss efforts to build new and unique datasets for better natural language understanding from all parts of the world.

  • Confronting a Changing World: Using Ultralow Precision to Detect Spatiotemporal Environmental Changes with Impacts on Food, Energy, and Pandemics

    • Daniel Jacobson, Chief Scientist for Computational Systems Biology, Oak Ridge National Laboratory

    In this session, you’ll learn how predicted growth in world population will put unparalleled stress on the need for sustainable energy and global food production, and also increase the likelihood of future pandemics. Find out how we develop novel climatype similarity methods to find high-order relationships between climate zones at high geospatial resolution.

See session highlights from distinguished scientists and their discoveries from the previous GTC. Get ready for what’s to come.

Find the complete GTC On-Demand playlist here.

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