Machine Learning for Spectroscopy

The integration of Machine Learning (ML) techniques into spectroscopy is revolutionizing the field, yet the intersection of these disciplines has not received the comprehensive exploration it deserves. This conference seeks to bridge that gap, aiming to catalyze significant advancements and foster deep interdisciplinary collaborations. The objectives of the conference are threefold: 

1. To reinforce and create new collaborations between researchers in spectroscopy, data scientists, and ML specialists. By bringing together experts from these fields, we aim to foster a collaborative environment that stimulates innovation and accelerates the development of new methodologies and applications.
2. To provide a forum for the exploration of ML applications in spectroscopy, focusing on advanced analysis and classification, data-driven spectral prediction, and emerging applications across various fields. This includes delving into novel ML techniques, sharing cutting-edge research, and discussing practical applications that can drive the field forward.
3. To produce the first edited volume devoted specifically to the intersection of ML and
   spectroscopy. This volume will serve as a comprehensive reference, compiling pioneering research and insights from the conference, and will be an invaluable resource for researchers and practitioners in the field.

Keynote talks will be delivered by leading experts in the field, providing valuable insights and fostering engaging discussions. These sessions will cover the latest advancements and future directions, setting the stage for in-depth exploration and collaboration. Invited speakers will present application-oriented research and encourage lively interaction and discussion among participants.

This conference is not just an academic gathering but a catalyst for future research and innovation. By prioritizing the inclusion of female scientists, young students, and early career researchers, and by ensuring a diverse representation of international experts, we aim to create an inclusive and dynamic environment. This will not only expand our network in Germany and Belgium, but also strengthen existing collaborations and establish new ones.

Further information