S. (Saba) Amiri
Faculty of Economics and Business
Section Accounting
Visiting address
- Plantage Muidergracht 12
Postal address
-
Postbus 15953
1001 NL Amsterdam
Contact details
-
Publications
2025
Allaart, C., Amiri, S., Bal, H., Belloum, A., Gommans, L., Van Halteren, A., & Klous, S. (2025). Private and Secure Distributed Deep Learning: A Survey. ACM Computing Surveys, 57(4), Article 92. https://doi.org/10.1145/3703452 [details]- Müller, T., Turner, R. J., Amiri, S., Allaart, C., van Binsbergen, L. T., Dijksman, L., van Engers, T., Belloum, A., Grosso, P., Grünwald, P., Hoogoort, K., Härmä, A., Hegeman, J. M., Kassem, J. A., Kebede, M., de Laat, C., van der Nat, P., Pals, A., Scheepers, F., & Klous, S. (2025). Optimizing Clinical Pathways with Federated Data. Jusletter IT, 2025, 147-158. https://doi.org/10.38023/eeb1b383-86b0-4b9e-89d5-57af4b58eeb3
2024
- Kassem, J. A., Amiri, S., Müller, T., Belloum, A., Grunwald, P., Grosso, P., Klous, S., Allaart, C., Kebede, M., Turner, R., van Binsbergen, L. T., van Halteren, A., & de Laat, C. (2024). Building a Digital Health Twin for Personalized Intervention: The EPI Project. In B. R. Haverkort, A. de Jongste, P. van Kuilenburg, & R. D. Vromans (Eds.), Commit2Data Article 2 (OpenAccess Series in Informatics; Vol. 124). Schloss Dagstuhl - Leibniz-Zentrum für Informatik. https://doi.org/10.4230/OASIcs.Commit2Data.2024.2
- Yordanov, T. R., Ravelli, A. C. J., Amiri, S., Vis, M., Houterman, S., Van der Voort, S. R., Abu-Hanna, A., & NHR THI Registration Committee (2024). Performance of federated learning-based models in the Dutch TAVI population was comparable to central strategies and outperformed local strategies. Frontiers in Cardiovascular Medicine, 11, Article 1399138. https://doi.org/10.3389/fcvm.2024.1399138 [details]
2022
- Amiri, S., Belloum, A., Nalisnick, E., Klous, S., & Gommans, L. (2022). On the impact of non-IID data on the performance and fairness of differentially private federated learning. In Proceedings, 52nd Annual IEEE/IFIP International Conference on Dependable Systems and Networks Workshop volume: 27-30 June 2022, Baltimore, Maryland (pp. 52-58). (DSN-W; Vol. 2022). IEEE Computer Society. https://doi.org/10.1109/DSN-W54100.2022.00018 [details]
- Amiri, S., Nalisnick, E., Belloum, A., Klous, S., & Gommans, L. (2022). Generating Heavy-Tailed Synthetic Data with Normalizing Flows. In The 5th Workshop on Tractable Probabilistic Modeling https://openreview.net/forum?id=PbvyJ8XpNn
2021
- Amiri, S., Belloum, A., Klous, S., & Gommans, L. (2021). Compressive differentiallyprivate federated learning through universal vector quantization. In AAAI Workshop on Privacy-Preserving Artificial Intelligence AAAI.
2019
- Amiri, S., Salimzadeh, S., & Belloum, A. S. Z. (2019). A survey of scalable deep learning frameworks. In IEEE 15th International Conference on eScience: proceedings : 24-27 September 2019, San Diego, California (pp. 650-651). IEEE Computer Society. https://doi.org/10.1109/eScience.2019.00102 [details]
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Ancillary activities
No ancillary activities
Allaart, C., Amiri, S., Bal, H., Belloum, A., Gommans, L., Van Halteren, A., & Klous, S. (2025). Private and Secure Distributed Deep Learning: A Survey. ACM Computing Surveys, 57(4), Article 92.