Milica Todorovic
milica.todorovic@utu.fi +358 29 450 3619 +358 50 535 9519 : 302 My phone number is +358 50 331 0029. : https://orcid.org/0000-0003-0028-0105(external) |
computational materials science; first principles simulations; hybrid organic/inorganic materials; surface science; artificial intelligence; data science; Bayesian optimization
I lead the Materials Informatics Laboratory group at UTU. My research combines aritifical intelligence algorithms and first-principles simulations with the objective to optimize functional materials and their performance in devices. At MIL, we purpuse data-driven solutions across disciplines, from aerosol research to chemical engineering bio-based materials, from computation to experiment.
Service:
Vice-director of Sustainable Materials and Manufacturing (SUSMAT) (external)UTU profiling area
Vice-chair of COST Action CA22154 - Data-driven Applications towards the Engineering of functional Materials: an Open Network (DAEMON)(external)
Vice-leader of Human-Centric Artificial Intelligence for Sustainable Future (HAIF)(external), Doctoral Training Network
Co-lead of Finnish Centre for AI (FCAI)(external) Highlight E: Data-driven design of materials
Head of the Modern Industrial Materials MSc track(external)
MTEK0023 Data Visualisation and Analysis
MTEK0023 Simulations and New Materials
MTEK0024 Machine Learning for Materials Science
- Active learning of molecular data for task-specific objectives (2025)
- Journal of Chemical Physics
- An innovative data-driven approach to the design and optimization of battery recycling processes (2025)
- Chemical Engineering Journal
- Active learning for data-efficient optimisation of functional materials (2024) Todorović, Milica
- Active learning for data-efficient optimisation of materials and processes (2024) Todorović, Milica
- Active Learning for Surface Adsorption Chemistry (2024) 11th Triennial Congress of the International Society for Theoretical Chemical Physics Todorović, Milica
- Active Learning of Microstructure-Property Relations in Hybrid Materials (2024) Todorović, Milica
- Application of the Question Answering method to extract information from materials science literature (2024) Sipilä, Matilda; Mehryary, Farrokh; Pyysalo, Sampo; Ginter, Filip; Todorović Milica
- Data digitalization strategies for AI-driven experimentation (2024) Zniber, Mohammed; Todorović, Milica
- Data-driven multimodal XPS study of molecular adsorbates on atmospheric aerosol nanoparticles (2024) Adhyatma, Abdurrahman; Das, Mandira; Lin, Jack; Prisle, Nønne; Todorović, Milica
- Decoding Surface Adsorption Chemistry with Active Learning (2024) The 10th International Symposium on Surface Science (ISSS-10) Todorović, Milica
- First-Principles Structure Search Study of 17-β-Estradiol Adsorption on Graphene (2024)
- ACS Omega
- From Text to Graphs—Visualizing Materials Space with ForceAtlas2 and MEGnet (2024) Galica, Tomasz; Sipilä, Matilda; Todorović, Milica
- High-Yield WS2 Synthesis through Sulfurization in Custom-Modified Atmospheric Pressure Chemical Vapor Deposition Reactor, Paving the Way for Selective NH3 Vapor Detection (2024)
- ACS Applied Materials and Interfaces
- Question Answering models for information extraction from perovskite materials science literature (2024) 2024 MRS Fall Meeting and Exhibit Sipilä, Matilda; Mehryary, Farrokh; Pyysalo, Sampo; Ginter, Filip, Todorović, Milica
- Structural Disorder by Octahedral Tilting in Inorganic Halide Perovskites: New Insight with Bayesian Optimization (2024)
- Small Structures
- The search for sparse data in molecular datasets: Application of active learning to identify extremely low volatile organic compounds (2024)
- Journal of Aerosol Science
- Visual representation of materials and their properties (2024) Galica, Tomasz; Sipilä, Matilda; Todorović, Milica
- XPS spectra of atmospheric aerosols: A combined DFT and ML approach (2024) Adhyatma, Abdurrahman; Das, Mandira; Lin, Jack; Prisle, Nønne; Todorović, Milica
- Atomic structures, conformers and thermodynamic properties of 32k atmospheric molecules (2023)
- Scientific Data
- Comparing methods for the long-term performance assessment of bifacial photovoltaic modules in Nordic conditions (2023)
- Renewable Energy
