Overview
The IAI Center aims to bring about innovation to impact the potential of Artificial Intelligence to industrial applications. Special focus on prognostics and health management, and predictive metrology for monitoring of quality and reliability of industrial systems.
Research Focus
Develop non-traditional machine learning techniques for highly-connected and complex engineering systems, including transfer learning, domain adaptation, topological data analytics, stream of quality (SoQ) process virtual metrology, similarity-based machine learning, etc.
Develop the industrial large knowledge model (ILKM) for RAG augmented LLM techniques.
Key Initiatives
NIST CHIPS Act funded research on SoQ methodology for yield improvement of semiconductor manufacturing.
Dept of Education funded research on modeling and simulation of metaverse and digital twin-based machine learning Tools.
Industrial membership funded research on non-traditional machine learning technologies and data foundry for rapid AI development and deployment.
Industrial AI courses for talent development and workforce training.