May 20-23, 2024 | Virtual Conference
March 31, 2024 | Registration Deadline
Registration is now closed. If you received an invitation, please, check email for password or contact organizers.
Check back for future events! 🧪💻
Summary
We are thrilled to announce Machine Learning in Chemical and Materials Sciences 2024 conference, a platform to showcase your ML research and connect with the renowned experts of the field.
The integration of Machine Learning (ML) techniques into chemistry and materials science has brought about transformative advancements, boosting the pace and precision of predictions. Notable breakthroughs encompass property predictions for materials, the reverse and forward engineering of tailor-made molecules, the creation of transferable interatomic potentials, the formulation of differentiable physics models, intelligent exploration of chemical space, and the rationalization of experimental observations, to name just a few success stories.
Topics
• ML Methods for Exploring Non-Equilibrium Processes
• Best Practices in Data Collection
• Meta-Learning Models and Heterogeneous Data Sources
• Development of Differentiable Physics Models
• ML-Assisted Material Design and Search
Registration
This is a virtual only event with free ($0) registration. Please, use the link to register. If you have any questions, please contact:
| Nikita Fedik | nfedik@lanl.gov |
| Vidushi Sharma | vidushi@lanl.gov |
Organizers:
| Nikita Fedik | LANL T-1/CNLS |
| Vidushi Sharma | LANL T-1/CNLS |
Organizing Committee:
| Ben Nebgen | LANL T-1 |
| Kipton Barros | LANL T-1 |
| Ying Wai Li | LANL CCS-7 |
| Ping Yang | LANL T-1 |
| Enrique Batista | LANL CNLS |
| Nicholas Lubbers | LANL CCS-3 |
| Danny Perez | LANL T-1 |
| Sergei Tretiak | LANL T-1/CINT |
