Spectroscopic techniques have been instrumental in improving our understanding of the structure of complex materials. However, interpreting experimental spectra often remains challenging due to overlapping signals and the reliance on simplified theoretical references. Over the past decades, quantum-mechanical simulations have become indispensable for predicting and interpreting experimental spectra, thanks to advances in electronic-structure-based methods. 

Today, the field is evolving rapidly: low-scaling algorithms, high-throughput methodologies, and machine learning techniques are transforming how we predict and interpret spectra, bridging the gap between theory and experiment. 

This workshop aims to bring together the computational spectroscopy community to discuss recent breakthroughs, open challenges, and future directions. 

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Key Topics 

• Highly accurate electronic-structure techniques 

• High-throughput spectrum generation and materials screening 

• Machine learning for accelerating predictions and interpreting experimental spectra 

• Structure inference from spectral data 

• Novel approaches combining experimental and simulated spectra 

• Applications to functional materials, such as catalysts, energy storage systems and quantum materials 

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Why Attend? 

This event is more than a technical meeting—it’s an opportunity to foster dialogue between theory and experiment, build collaborations, and strengthen an interdisciplinary community driving innovation in different spectroscopy fields. 

We have invited leading international experts, both theorists and experimentalists, to share insights and inspire new ideas. 

Looking forward to seeing you in Modena! Join us for an engaging workshop filled with knowledge exchange, innovation, and networking! 

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Supported by

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