Mechanical and AI Lab
MAIL applies AI and machine learning to mechanical engineering to improve prediction and optimization. It develops data-driven models that blend physics with learning algorithms and uses multi-scale simulations (CFD, MD, DFT) for data generation. Key applications include design optimization, predictive maintenance, quality control, autonomous systems, and energy management. The work spans academia and industry, with technologies including CFD, MD, DFT, machine learning, and computer vision.
Mechanical and AI Lab
MAIL applies AI and machine learning to mechanical engineering to improve prediction and optimization. It develops data-driven models that blend physics with learning algorithms and uses multi-scale simulations (CFD, MD, DFT) for data generation. Key applications include design optimization, predictive maintenance, quality control, autonomous systems, and energy management. The work spans academia and industry, with technologies including CFD, MD, DFT, machine learning, and computer vision.