Tristan Bereau

Tristan Bereau is a Principal Investigator at the Institute for Theoretical Physics (ITP) of Heidelberg University. His research focuses on computational methods for understanding molecular systems, including coarse-grained modeling, machine learning-driven materials discovery, and membrane dynamics. He leads projects on drug-membrane interactions, peptide structures, and data-centric approaches in materials science. His work emphasizes reproducibility and software development, as seen in tools like Martignac for coarse-grained simulations.

Key research themes include exploring chemical space through high-throughput screening, optimizing crystal structures with data-driven methods, and analyzing membrane asymmetries using advanced simulations. He advocates for FAIR (Findable, Accessible, Interoperable, Reusable) data principles to enhance scientific collaboration and transparency.

His contributions span interdisciplinary areas, such as integrating machine learning with thermodynamic integration for free-energy calculations and designing antimicrobial peptides via computational screening. Collaborations bridge computational physics, chemistry, and biology, addressing challenges in drug delivery, materials design, and viral infectivity mechanisms.