Notre Dame hosts major international artificial intelligence and machine learning conference
Experts from 22 different institutions of education and research located in 7 different countries gathered at the University of Notre Dame (South Bend, Indiana, USA) last week for a flagship workshop of the Centre Européen de Calcul Atomique et Moléculaire (CECAM). From July 7 to 9, 2025, the participants—who are among the world's top researchers in the development and application of artificial intelligence (AI) and machine learning for chemistry and materials discovery—gathered for presentations, a poster session, and discussions focused on machine learning advances for the prediction of molecular and material properties.
“This was a unique opportunity to bring together so many experts in the field from all over the world right here at Notre Dame,” said Yamil Colón, associate professor in the Department of Chemical and Biomolecular Engineering. “Our students were able to participate in the poster sessions and share ideas with world-class peers. This week was a great moment for all of us to get together, to network, and to share science.”
The workshop marks only the second occasion that CECAM has convened in the United States. Founded in 1969 and headquartered in Lausanne, Switzerland, CECAM’s US-Central node was established at the University of Chicago in 2023, with Notre Dame as one of its founding partners. With 21 nodes encompassing 29 institutions from 17 countries, CECAM meets regularly to share findings and best practices in computational science organized around a timely theme.
“Machine learning, the focus of this workshop, is revolutionizing the field of computational predictions of molecular and material properties. It has enabled recent advances like foundation models and machine learning interatomic potentials,” said Colón, who served as one of the workshop’s organizers.
In recent years, machine learning has become a powerful tool for predicting the properties of chemical structures and engineered materials without the need for wet lab experiments, which can be time-consuming and hazardous. Advances in computer engineering have allowed researchers to develop algorithms that can extract chemical attributes and predict properties from atomic coordinates and feature vectors. Experts have also devoted much effort to compiling large property datasets, which are critical for the training and standardizing of new frameworks.
To date, machine learning models have been successfully applied to the prediction of reactive, physicochemical, and pharmacological properties of molecules and materials. Researchers have also implemented machine learning in spectroscopy, which enables the automated characterization of a variety of chemical spectra, including infrared (IR), ultraviolet and visible light (UV/vis), and nuclear magnetic resonance (NMR).
“Machine learning advancements open the door for accelerating chemical and materials characterization in the immediate future,” explained Colón. “With a new understanding of physical, chemical, and molecular phenomena that were once unattainable, there is high potential for the development of novel materials to address issues in energy, water security, and healthcare, as well as a new generation of drug development."
“This workshop facilitated a great exchange of information on the latest developments in this fast-moving research area,” said Ed Maginn, associate vice president for research and Keough-Hesburgh Professor in the Department of Chemical and Biomolecular Engineering, who helped organize the workshop. “I’m very excited that Notre Dame was able to host such an exceptional group of scholars for a rich week of international collaboration in this crucial field.”
The workshop was made possible by financial support from CECAM as well as the following Notre Dame entities: Berthiaume Institute for Precision Health; Center for Research Computing; College of Engineering; College of Science; Department of Chemical and Biomolecular Engineering; Department of Chemistry and Biochemistry; Institute for Latino Studies; Lucy Family Institute for Data & Society; ND Energy; NDnano; Notre Dame Research; Scientific Artificial Intelligence Initiative.
To learn more about machine learning and artificial intelligence research at the University of Notre Dame, please visit the Center for Research Computing, Lucy Family Institute for Data & Society, and Scientific Artificial Intelligence Initiative.
Contact
Erin Fennessy / Writing Program Manager
Notre Dame Research / University of Notre Dame
efenness@nd.edu / +1 574-631-8183
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Photos
Photos by Angelic Rose Hubert.
About Notre Dame Research
The University of Notre Dame is a private research and teaching university inspired by its Catholic mission. Located in South Bend, Indiana, its researchers are advancing human understanding through research, scholarship, education, and creative endeavor in order to be a repository for knowledge and a powerful means for doing good in the world. For more information, please visit NDR's website or NDR's LinkedIn.
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