معرفی
Milica Todorovic is a Visiting Professor at Aalto University's Department of Applied Physics, leading machine learning research within the Computational Electronic Structure Theory (CEST) group. Her work bridges quantum mechanical simulations and machine learning algorithms to optimize material functionality, particularly for solar cell components and organic-inorganic interfaces.
Research Interests include:
- Data-driven materials science
- Active learning for molecular datasets
- Bayesian optimization in atomic structure prediction
- Quantum simulations of surfaces and adsorbates
- Thermodynamic property modeling for atmospheric molecules
Article Trends (2017-2025) show focus on machine learning applied to materials science, with subfields spanning bayesian optimization, conformational analysis, and density functional theory. Key collaborations include Patrick Rinke and Hanna Vehkamäki.
Activities include organizing workshops like the Young Researcher’s Workshop on Machine Learning for Materials Science (2019) and International Workshop on Machine Learning for Materials Science (2018).
