Industrial AI Laboratory


Research Area

I Physics-guided AI for Digital Twins

The IAI Lab focuses on the development of novel physics-guided artificial intelligence (AI), aiming to develop neural computational methods with unprecedented performance. We study diverse methods for hybridizing the AI framework and our engineering knowledge with expansive physics models, providing the fidelity and adaptability of data-driven methods for a variety of domains. Our research offers the potential for versatile digital-twin applications that require real-time, accurate, interactive, and interpretable analyses.

I Mechanism-inspired Deep Neural Networks

We develop novel deep neural networks that are intrinsically inspired by the underlying mechanisms of engineering systems. Our aim is not only to achieve high predictive performance but also to enhance interpretability in a way that aligns with physical phenomena. This innovative method advances the field of neural network research and opens up new possibilities for creating more intuitive and explainable applications across a range of scientific and engineering disciplines