Weilong Chen

Weilong Chen is a researcher at the Multiscale Modeling of Fluid Materials group in the School of Mechanical Engineering at Technical University of Munich (TUM). He is affiliated with the Atomistic Modeling Center (AMC) and Munich Data Science Institute (MDSI), working on computational methods for fluid materials and molecular simulations.

• Education: MSc in Mathematics (2024, Chalmers University, Sweden) and BSc in Aerospace Engineering (2022, National University of Defense Technology, China)

His research focuses on AI for Science, particularly Graph Neural Networks, Deep Generative Models (including Flow Matching/Diffusion), and Machine Learning Potentials for applications in Coarse-grained Molecular Dynamics and scalable simulations. Recent work involves developing frameworks like chemtrain-deploy for million-atom molecular dynamics and generative thermodynamics modeling.

He actively collaborates on projects at the intersection of machine learning and physics-based modeling, with involvement in workshops and team events. Weilong Chen is available for master's thesis supervision and can be contacted via email.