Data Science
Edmond Scientific provides a comprehensive range of data sciences expertise, support and services across a range of industries and applications.
In Artificial Intelligence and Machine Learning (AI/ML), we perform research and develop models and modeling architectures that utilize physics-based models that are optimized with Machine Learning (ML) and Artificial Intelligence (AI) techniques to reduce computational requirements and also reduce the need for training data. Reducing computational requirements allows us to use the model to support real-time analyses when combined with in-situ sensors.
For High Performance Computing (HPC) and Supercomputing environments that process both data and images, we support R&D, architecture, and system improvements for Next Generation Flexible computing environments and load balancing.
Artificial Intelligence and Machine Learning (AI/ML) Applications
- Cognitive and In-Situ Sensors
- Real-Time Manufacturing Quality Control
- Hybrid Multi-Model Architectures
- Physics-Informed Neural Networks (PINNs)
- Error Handling and Defect Mitigation Applications
- Data and Image Special Interest Models
Edmond Scientific’s interdisciplinary skills combine mathematics, statistics, software engineering, and domain expertise to extract meaningful, actionable insights from data.
High Performance Computing (HPC)
- Develop and Apply Computational, Developmental, Model Integration, and Equivalence Evaluation Standards
- Develop and Apply Framework and Coupling Standards and Mechanisms to Manage Workflow
- Estimate and Optimize Model Operations for Memory, Communication, and Computation Demands
- Automatically Analyze and Configure Model Algorithms for Arbitrary Clusters and Core Connectivity
- Generate, Dynamically Update, and Execute Model Task Allocation Tables (TATs)
- Implement Effective Domain Partition Algorithms
- Dynamically Manage Computing Resources, Data Storage, and Buffers
