
About
Janus Juul Eriksen is an Associate Professor in the Department of Chemistry at the Technical University of Denmark (DTU), actively engaged in quantum chemistry research and PhD supervision. His work bridges theoretical developments with practical applications in electronic structure theory and computational chemistry.
Dr. Eriksen's research focuses on quantum chemistry methods, particularly electronic structure theory, many-body physics, and machine learning applications in chemistry. His fingerprint analysis shows significant contributions to Molecular Orbital Chemistry (100%), Atomic Orbital Chemistry (57%), Electronic State Chemistry (42%), and Density Functional Theory (28%). His work develops advanced computational techniques for analyzing electronic properties of molecules and materials with applications in materials design and catalysis.
His recent publications demonstrate expertise in atomic decompositions, active space methods, and neural networks for chemical applications. Key works include 'Atomic Decompositions of Periodic Electronic-Structure Simulations' (2025), 'MBE-CASSCF Approach for the Accurate Treatment of Large Active Spaces' (2024), and 'Transferability of atom-based neural networks' (2024), showing his leadership at the intersection of quantum chemistry and machine learning.
Dr. Eriksen currently supervises three PhD students on projects related to electronic structure simulations in composite phases, decomposed machine learning in quantum chemistry, and mean-field decompositions of solid-state systems. His research has practical applications in materials design, catalysis, and understanding fundamental chemical properties as indicated by project keywords including 'Novel Material 100%', 'Materials Design 100%', and 'Chemical Property 100%'.
Beyond technical research, Dr. Eriksen contributes to academic policy discussions in Denmark, with publications addressing university reform, research policy, and academic freedom, demonstrating his engagement with broader scholarly and societal issues.
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