Milica Milovanović | Operations Research | Excellence in Research Award

Published on by Math Scientist

Prof. Milica Milovanović | Operations Research | Excellence in Research Award

Master Transportation Engineer | Faculty of Transport and Traffic Engineering, University of Belgrade | Serbia

Prof. Milica Milovanović, affiliated with the Faculty of Transport and Traffic Engineering at the University of Belgrade, specializes in transport safety, risk analysis, and decision-making methodologies in aviation and road traffic systems. Her research focuses on evaluating the Value of Statistical Life (VSL) in transport accidents, optimizing safety measures in aviation operations, and conducting risk assessments involving UAVs, drones, and logistics systems.
She frequently applies advanced multi-criteria decision-making (MCDM) models, hybrid assessment techniques, and quantitative risk frameworks. Her work contributes to improved safety policies, evidence-based investment decisions, and the development of safer, more efficient air and road transport systems.

Profiles: Scopus | Orcid

Featured Publications

Milovanović, M., Vujačić Petrović, J., Čokorilo, O., Vasov, Lj., Mirosavljević, P. D., & Stojiljković, B. (2025). Analysis of the value of statistical life in traffic accidents based on investments evaluation. Tehnika. https://doi.org/10.5937/tehnika2502223M

Snežana Tadić, Milovanović, M., Krstić, M., & Čokorilo, O. (2025). Selection of safety measures in aircraft operations: A hybrid Grey Delphi–AHP–ADAM MCDM model. Eng. https://doi.org/10.3390/eng6110295

Milovanović, M., Čokorilo, O., Ivković, I., Stojiljković, B., & Vasov, Lj. (2024). The value of statistical life in air and road transport. Aircraft Engineering and Aerospace Technology. https://doi.org/10.1108/aeat-01-2024-0019

Marina, M., Čokorilo, O., Mirosavljević, P., Vasov, Lj., Stojiljković, B., & Milovanović, M. (2024). Analysis of the impact of UAV collision on a commercial aircraft. In 2024 6th International Conference on Control Systems, Mathematical Modeling, Automation and Energy Efficiency (SUMMA). https://doi.org/10.1109/summa64428.2024.10803713

Tadić, S., Krstić, M., Veljović, M., Čokorilo, O., & Milovanović, M. (2024). Risk analysis of the use of drones in city logistics. Mathematics, 12(8), 1250. https://doi.org/10.3390/math12081250

Vasso Papadimitriou | Cost Estimation Models | Best Researcher Award

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Dr. Vasso Papadimitriou | Cost Estimation Models | Best Researcher Award

Researcher | Aristotle University of Thessaloniki | Greece

Dr. Vasso Papadimitriou is a forward-thinking researcher specializing in artificial intelligence applications in construction engineering, with a focus on cost estimation, digital construction, and sustainable project management. Her research bridges engineering design, machine learning, and construction technology, developing intelligent tools to enhance decision-making accuracy in building renovation and infrastructure projects.

Affiliated with the Aristotle University of Thessaloniki and the University of Macedonia, Dr. Papadimitriou’s work contributes to advancing AI-driven predictive models that improve efficiency and reduce uncertainty in project budgeting and execution. She applies methods such as Artificial Neural Networks (ANNs), Radial Basis Functions (RBFs), and TOPSIS to optimize renovation cost forecasting, aligning with the United Nations Sustainable Development Goals (SDG 9 and SDG 17).

Her research has been published in high-impact journals indexed in Scopus, Web of Science (SCI-Expanded, ESCI), and Google Scholar, with growing recognition for her innovative use of computational models in sustainable engineering and design. Through her comparative analyses and model development, Dr. Papadimitriou contributes to the digital transformation of the construction industry, shaping the future of AI-powered engineering solutions.

Profiles: Scopus | Orcid | Google Scholar | Web of Science 

Featured Publications

Papadimitriou, V. E., & Aretoulis, G. N. (2024). A final cost estimating model for building renovation projects. Buildings, 14(4), 1072. Citation count: 8.

Papadimitriou, V. E., Aretoulis, G. N., & Papathanasiou, J. (2024). Radial Basis Function (RBF) and Multilayer Perceptron (MLP) comparative analysis on building renovation cost estimation: The case of Greece. Algorithms, 17(9), 390. Citation count: 4.

Papadimitriou, V. E., & Aretoulis, G. N. (2025). An innovative approach regarding efficient and expedited early building renovation cost estimation utilizing ANNs and the TOPSIS methodology. Algorithms, 18(11), 696. Citation count: —.

Papadimitriou, V., & Aretoulis, G. (2023). Neural network models as a cost prediction tool to prevent building construction projects from a failure—A literature review. Proceedings of the Erasmus+ PROSPER Project International Scientific Conference. Citation count: 1.