Acceleration and Analysis of Molecular Dynamics Simulation Using Machine Learning

Explore cutting-edge techniques for enhancing molecular dynamics simulations through machine learning in this virtual seminar presented by Prof. Kenji Yasuoka from Keio University, Japan. Delve into the innovative approaches for accelerating and analyzing molecular dynamics simulations, gaining insights into how machine learning algorithms can revolutionize computational chemistry and materials science. Learn about the latest advancements in combining traditional molecular dynamics methods with artificial intelligence to improve simulation efficiency and extract meaningful data. Discover potential applications of these techniques in various fields, including drug discovery, materials design, and understanding complex biological systems. This 42-minute talk, hosted by the Atoms® group, offers a comprehensive overview of the intersection between molecular dynamics and machine learning, providing valuable knowledge for researchers, students, and professionals in the field of computational science.

Kenji Yasuoka - Acceleration and Analysis of Molecular Dynamics Simulation using Machine Learning