We develop deep learning-based surrogate models that efficiently approximate complex structural analysis results, training neural networks on finite element data.
We leverage machine learning and metaheuristic optimization to automate structural design, creating intelligent systems that generate optimal designs automatically.
Our robotics research focuses on intelligent automation for construction sites by combining computer vision, robotics, and AI to improve safety and efficiency.
