Predictive Analytics: Using Machine Learning for Infrastructure Health
Predictive analytics for resilient grid and edge systems
4. E-Science & Research
IP Protection in the Grid: Securing Data in Shared Research Networks
Protecting research IP across grid, cloud, edge, and AI
Automated Workflows e-Science: Distributed Platforms
Streamlining e-Science workflows across cloud and edge
Metadata Standardization: The Secret to Interoperable Global Research
Metadata standards enable interoperable global research
Digital Twin Strategy: Using Infrastructure for Real-Time Simulations
From grid computing to real-time digital twin infrastructure
Strategies for Visualizing Petabyte-Scale Scientific Datasets
Practical strategies for visualizing petabyte scientific data
Global Research Networks: Building Collaborative Environments for e-Science
From Grid to Edge and AI: practical roadmaps for research
Physics at Scale: How Distributed Tech Powers CERN and Beyond
From Grid to Edge: powering CERN’s distributed future
Real-Time e-Science: Processing High-Velocity Research Data Streams
Real-time e-science: engineering research data streams
Data Lake Architecture: Evolving Storage for Distributed Analytics
Evolving data lake architecture from grid to edge AI