PhD Candidate
Vasiliki Choleva is a PhD candidate at the laboratory. Her publications concern humanitarian and commercial supply chains, including the digital transformation of humanitarian supply chains through the AidTech platform and automated machine learning (AutoGluon, TabPFN) for supply chain optimisation.
Publications
Journal Articles
Panagiotopoulos, A., Karyotis, V., Dimitrakopoulos, G. N., Choleva-Tsiringkaki, V., & Kourouthanassis, P. E. (2026). Demystifying the Digital Transformation of Humanitarian Supply Chains Through AidTech. Logistics, 10(5), 110. https://doi.org/10.3390/logistics10050110
@article{panagiotopoulos2026demystifying,
title = {Demystifying the Digital Transformation of Humanitarian Supply Chains Through AidTech},
author = {Apostolos Panagiotopoulos and Vasileios Karyotis and Georgios N. Dimitrakopoulos and Vassiliki Choleva-Tsiringkaki and Panos E. Kourouthanassis},
url = {https://doi.org/10.3390/logistics10050110},
doi = {10.3390/logistics10050110},
year = {2026},
date = {2026-01-01},
journal = {Logistics},
volume = {10},
number = {5},
pages = {110},
publisher = {Multidisciplinary Digital Publishing Institute},
abstract = {Background: Humanitarian campaigns are more popular with more initiatives organized than ever by public and private bodies. Simultaneously, more peculiar challenges, such as zero-waste and transparency, are required compared to traditional supply chains. This work investigates the current technological landscape for shaping the next generation of humanitarian aid management systems, focusing on algorithmic and operational aspects, matching them to a new architecture for a target-platform, called AidTech. Methods: The methodology follows a systematic literature coverage, identifying cross-disciplinary trends from operations research, computer science and sustainable logistics. We examine the convergence of optimization, artificial intelligence, and blockchain-enabled traceability toward efficient and transparent humanitarian logistics. The employed methods include adaptive scheduling, resource allocation algorithms and privacy–preserving collaboration for meeting special constraints imposed by the humanitarian scope. Results: The findings focus on the architectural perspective of humanitarian supply chains and highlight that modern humanitarian infrastructures will increasingly rely on hybrid optimization methods integrating graph theory, dynamic routing under stochastic demand, multi-criteria decision analysis and distributed ledger technologies. Conclusions: We conclude that these paradigms, when combined under a unified cyber–physical architecture, e.g., AidTech, can substantially improve responsiveness, equity and sustainability in crisis management, further shaping future humanitarian logistics.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Background: Humanitarian campaigns are more popular with more initiatives organized than ever by public and private bodies. Simultaneously, more peculiar challenges, such as zero-waste and transparency, are required compared to traditional supply chains. This work investigates the current technological landscape for shaping the next generation of humanitarian aid management systems, focusing on algorithmic and operational aspects, matching them to a new architecture for a target-platform, called AidTech. Methods: The methodology follows a systematic literature coverage, identifying cross-disciplinary trends from operations research, computer science and sustainable logistics. We examine the convergence of optimization, artificial intelligence, and blockchain-enabled traceability toward efficient and transparent humanitarian logistics. The employed methods include adaptive scheduling, resource allocation algorithms and privacy–preserving collaboration for meeting special constraints imposed by the humanitarian scope. Results: The findings focus on the architectural perspective of humanitarian supply chains and highlight that modern humanitarian infrastructures will increasingly rely on hybrid optimization methods integrating graph theory, dynamic routing under stochastic demand, multi-criteria decision analysis and distributed ledger technologies. Conclusions: We conclude that these paradigms, when combined under a unified cyber–physical architecture, e.g., AidTech, can substantially improve responsiveness, equity and sustainability in crisis management, further shaping future humanitarian logistics.
Proceedings Articles
Dimitrakopoulos, G. N., Vrahatis, A. G., Choleva, V., Korfiatis, N., Karyotis, V., & Kourouthanassis, P. E. (2025). AutoGluon and TabPFN for Supply Chain Optimization. In 2025 IEEE International Conference on Big Data (BigData). Macau, China: IEEE.
@inproceedings{dimitrakopoulos2025autogluon,
title = {AutoGluon and TabPFN for Supply Chain Optimization},
author = {Georgios N. Dimitrakopoulos and Aristidis G. Vrahatis and V. Choleva and Nikolaos Korfiatis and Vasileios Karyotis and Panos E. Kourouthanassis},
year = {2025},
date = {2025-01-01},
booktitle = {2025 IEEE International Conference on Big Data (BigData)},
publisher = {IEEE},
address = {Macau, China},
note = {IEEE BigData 2025, December 8-11, 2025, Macau, China},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}