Molecular Simulation in the Age of Artificial Intelligence
Machine learning and deep neural networks boost ab-initio molecular dynamics simulations, enabling first-principles predictions where only semiempirical models were viable. Two examples at vastly different scales illustrate the concept.
On June 29, 2026, BIFOLD invites participants to the event “Molecular Simulation in the Age of Artificial Intelligence” in Berlin. The session explores recent developments at the intersection of artificial intelligence, physics, and chemistry, highlighting how data-driven approaches are transforming scientific simulation.
The focus is on the use of machine learning and deep neural networks to enhance ab-initio molecular dynamics simulations. Through examples across different physical scales, the talk demonstrates how AI-based models enable more accurate predictions and provide deeper insights into chemical and physical processes. At the same time, it emphasizes the continued importance of theoretical understanding and physical intuition in model development.
The lecture will be delivered by Prof. Roberto Car (Princeton University), a leading physicist and co-inventor of ab-initio molecular dynamics. The event is aimed at researchers and practitioners interested in AI-driven simulation and its applications in the natural and material sciences.
• Date: June 29, 2026
• Time: 2:00 PM – 3:00 PM
• Location: BIFOLD, 7th Floor, Room 701, Franklinstr. 28/29, 10587 Berlin
• Organizer: BIFOLD
• Admission: (free, registration recommended)
• Focus: AI in simulation, molecular dynamics, physics, chemistry
• Audience: researchers, students, and professionals in AI, physics, chemistry, and materials science