Egor Rumiantsev

Egor Rumiantsev is a Doctoral Assistant at the Laboratory of Computational Science and Modelling (COSMO) within the Institute of Mechanical Engineering (IMX) at École Polytechnique Fédérale de Lausanne (EPFL). He is concurrently enrolled in the Doctoral Program in Materials Science and Engineering under the École Doctorale de Mécanique (EDMX). His research focuses on advancing computational methods for materials science through machine learning integration, quantum chemistry, and atomistic simulations.

Research Interests: Egor’s work emphasizes developing neural network models for molecular property prediction, optimizing long-range atomistic simulations, and exploring doping effects in materials like FeRh alloys. His projects bridge machine learning innovations with traditional computational chemistry techniques to enhance predictive accuracy and scalability.

Recent Contributions: Key works include LAGNet (2025) for electron density prediction, advancements in reinforcement learning for molecule generation (FREED++), and studies on FeRh alloy doping mechanisms. These reflect his commitment to interdisciplinary approaches in computational materials science.

Labs/Teams: COSMO Lab at EPFL, collaborating on cutting-edge computational modeling projects within the IMX Institute.