Laser Induced

Laser-induced processes are being extensively investigated for applications ranging from material processing and surgery to combustion control. Current research focuses on improving the precision and efficiency of these processes through advanced modeling and control techniques, employing machine learning algorithms like neural networks (including convolutional and recurrent architectures) and model predictive control to optimize laser parameters and compensate for dynamic factors such as tissue movement or material inhomogeneity. These advancements are driving improvements in minimally invasive surgery, enabling more precise material ablation, and facilitating real-time feedback control for enhanced safety and efficacy.