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PAPAVASILEIOU Paris

Main Referenced Co-authors
KORONAKI, Eleni  (5)
BORDAS, Stéphane  (4)
Boudouvis, Andreas G. (4)
Czettl, Christoph (4)
Kathrein, Martin (4)
Main Referenced Keywords
Chemical Engineering (all) (2); Chemical Vapor Deposition (2); chemical vapor deposition (2); Chemical vapour deposition (2); Chemistry (all) (2);
Main Referenced Disciplines
Chemical engineering (5)
Computer science (1)
Physical, chemical, mathematical & earth Sciences: Multidisciplinary, general & others (1)

Publications (total 6)

The most downloaded
56 downloads
PAPAVASILEIOU, P., FARINA, S., KORONAKI, E., BOUDOUVIS, A., BORDAS, S., & SKUPIN, A. (2024). Machine Learning-based Predictions of Spatial Metabolic Profiles Demonstrate the Impact of Morphology on Astrocytic Energy Metabolism. (preprint). ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/62074. doi:10.1101/2024.09.18.613725 https://hdl.handle.net/10993/62074

The most cited

11 citations (WOS)

PAPAVASILEIOU, P., KORONAKI, E., POZZETTI, G., Kathrein, M., Czettl, C., Boudouvis, A. G., & BORDAS, S. (August 2023). Equation-based and data-driven modeling strategies for industrial coating processes. Computers in Industry, 149, 103938. doi:10.1016/j.compind.2023.103938 https://hdl.handle.net/10993/57198

PAPAVASILEIOU, P., Giovanis, D. G., POZZETTI, G., Kathrein, M., Czettl, C., Kevrekidis, I. G., Boudouvis, A. G., BORDAS, S., & KORONAKI, E. (January 2025). Integrating supervised and unsupervised learning approaches to unveil critical process inputs. Computers and Chemical Engineering, 192, 108857. doi:10.1016/j.compchemeng.2024.108857
Peer reviewed

LOACHAMIN SUNTAXI, G., PAPAVASILEIOU, P., KORONAKI, E., Giovanis, D. G., Gakis, G., Aviziotis, I. G., Kathrein, M., POZZETTI, G., Czettl, C., Bordas, S. P. A., & Boudouvis, A. G. (15 November 2024). Discovering deposition process regimes: Leveraging unsupervised learning for process insights, surrogate modeling, and sensitivity analysis. Chemical Engineering Journal Advances, 20, 100667. doi:10.1016/j.ceja.2024.100667
Peer reviewed

PAPAVASILEIOU, P. (2024). HYBRID EQUATION-BASED AND DATA-DRIVEN COMPUTATIONAL WORKFLOWS FOR ANALYSIS AND PREDICTION OF INDUSTRIAL DEPOSITION PROCESSES [Doctoral thesis, Unilu - Université du Luxembourg]. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/63001

PAPAVASILEIOU, P., FARINA, S., KORONAKI, E., BOUDOUVIS, A., BORDAS, S., & SKUPIN, A. (2024). Machine Learning-based Predictions of Spatial Metabolic Profiles Demonstrate the Impact of Morphology on Astrocytic Energy Metabolism. (preprint). ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/62074. doi:10.1101/2024.09.18.613725

PAPAVASILEIOU, P., KORONAKI, E., POZZETTI, G., Kathrein, M., Czettl, C., Boudouvis, A. G., & BORDAS, S. (August 2023). Equation-based and data-driven modeling strategies for industrial coating processes. Computers in Industry, 149, 103938. doi:10.1016/j.compind.2023.103938
Peer Reviewed verified by ORBi

PAPAVASILEIOU, P., KORONAKI, E., POZZETTI, G., Kathrein, M., Czettl, C., Boudouvis, A. G., Mountziaris, T. J., & BORDAS, S. (October 2022). An efficient chemistry-enhanced CFD model for the investigation of the rate-limiting mechanisms in industrial Chemical Vapor Deposition reactors. Chemical Engineering Research and Design, 186, 314 - 325. doi:10.1016/j.cherd.2022.08.005
Peer Reviewed verified by ORBi

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