Raman System

Raman spectroscopy, a technique analyzing molecular vibrations via light scattering, is increasingly used for diverse applications by leveraging machine learning to analyze complex spectral data. Current research focuses on improving the accuracy and robustness of Raman-based analyses through advanced machine learning models, including convolutional neural networks (CNNs), autoencoders, and tensor networks, often coupled with dimensionality reduction techniques like diffusion maps. This approach enables rapid, non-destructive chemical identification and quantification across fields like biomedical diagnostics, environmental monitoring, and materials science, offering significant potential for improved analytical capabilities and automation.