Propelling Higher Education Beyond the Status Quo

Manchester physicists David Topping and Hao Zhang applied NVIDIA Earth-2 generative models to air quality forecasting — unlocking predictions fast enough to inform public health.

Stanford University partnered with NVIDIA and Mark III Systems to design and deploy the Marlowe DGX SuperPOD as a campus-wide, GPU-optimized research platform that complements Stanford’s existing Sherlock Computing Cluster resources. This enables researchers across all seven schools to scale AI and data-driven workloads.

The National Science Foundation’s National Artificial Intelligence Research Resource (NAIRR) pilot program with access to NVIDIA DGX™ Cloud, The Walter Lab at Harvard Medical School completed nearly 1.7 million protein interaction predictions in 3 months.

Researchers at The Ohio State University are digitizing living organisms for broad science and conservation efforts through BioCLIP 2—a Tree of Life foundation model for half of the world’s named species. Built using NVIDIA A100 and H100 GPUs, it achieves the best or top-two performance for species identification and zero-shot recognition across almost one million taxa. The model unlocks emergent ecological and evolutionary insights and was recently featured at NeurIPS.

Researchers at Argonne National Laboratory and collaborating institutions have developed RADAR, a federated, privacy-enhancing framework that enables observatories to coordinate gravitational-wave and radio follow-up without moving or exposing proprietary data. Running on NVIDIA-accelerated supercomputing systems, RADAR demonstrates how multi-messenger discovery can be accelerated through secure, cross-observatory workflows that preserve data ownership.

Researchers at the University of Michigan developed Diff-SPORT, which combines generative models with advanced inference to deliver scalable, interpretable urban flow simulations. The team merged computational fluid dynamics with AI platforms using NVIDIA PhysicsNeMo™, which provides the core infrastructure for diffusion models and physics-informed machine learning.

Researchers at the University of Maryland, recipients of a grant from the NVIDIA Academic Grant Program, are developing AI-powered humanoid systems capable of complex household tasks with greater autonomy. Using the NVIDIA Isaac™ open robotics development platform, they create photorealistic virtual home environments populated with diverse objects, allowing robots to practice millions of task variations and safely test rare or complex scenarios.

UC Santa Cruz Center for Coastal Climate Resilience focuses on modeling and mapping the benefits of coral reefs and mangroves for reducing flood risk, which helps inform adaptation and preservation efforts. The center uses NVIDIA CUDA-X™ software, including the cuPyNumeric library and nvfortran compiler, running on NVIDIA RTX™ GPUs awarded through the NVIDIA Academic Grant Program.

Smaller asteroids have been located farther out with the world’s most powerful space telescope, which can now also track the city crusher 2024YR4 asteroid with a 2.3% chance of hitting Earth.

A joint team at BRLi and National Polytechnic Institute of Toulouse (Toulouse INP), through a collaboration in the ANITI research institute, has designed an end-to-end AI approach that fully replaces the physics-based solver. This team includes expertise in both hydraulic modeling and AI methods for physics, enabling this interdisciplinary work. The Toulouse INP team then used these to train an end-to-end AI system to emulate the solver leveraging NVIDIA PhysicsNeMo from the Earth-2 platform.

Researchers used a deep learning model powered by an NVIDIA RTX A6000 GPU to automate spinal diagnostics, achieving 88% reliability for curvature predictions. The result: faster diagnoses, fewer errors, and better outcomes for patients with scoliosis and beyond.

The University of Florida’s AI infrastructure and supercomputer, the HiPerGator, is used to build a host of AI solutions to serve students, faculty, staff, and researchers. The university uses NVIDIA NIM microservices and Llama NIM on its HiPerGator supercomputer to bring a family of NaviGator chatbots providing capabilities of large language models (LLMs) to every facet of university life.

Colorado State University (CSU) cross-departmental collaboration between the Department of Electrical and Computer Engineering, Atmospheric Science, and the Cooperative Institute for Research in the Atmosphere (CIRA) recently trained a specialized NVIDIA Earth-2 StormScope Nowcasting model for operational severe hailstorm prediction.