Summary
Santiago Rigamonti is a senior research scientist based in Berlin with 12 years of focused experience in computational materials science and condensed matter physics. He develops and applies first-principles methods, cluster expansion techniques, and data-driven models to predict phase behavior, vacancy distributions, and electronic transport in functional materials. His work spans redox and catalytic chemistry, thermoelectrics, and quantum transport, often integrating machine learning and statistical mechanics to accelerate materials discovery. At Humboldt University of Berlin he leads multidisciplinary projects and contributes open-source Python tools (notably CELL and MADAS) that have broadened access to advanced materials modeling. Trained with a PhD from Instituto Balseiro and a postdoc at DIPC, he combines deep theoretical insight with practical software development to bridge simulation and experiment. Colleagues value his curiosity-driven approach and knack for turning complex many-body problems into reproducible, community-ready workflows.
12 years of coding experience
PhD, Physics, Physics, PhD, Physics, Physics at Instituto Balseiro
Bachelor's degree, Physics, Bachelor's degree, Physics at Universidad Nacional de La Plata
English, German, Spanish, Italian