Profil

DELGADO FERNANDEZ Joaquin

University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > FINATRAX

ORCID
0000-0003-1326-6134
Main Referenced Co-authors
POTENCIANO MENCI, Sergio  (4)
FRIDGEN, Gilbert  (3)
BARBEREAU, Tom Josua  (2)
LEE, Chul Min  (2)
PAVIĆ, Ivan  (2)
Main Referenced Keywords
artificial intelligence (2); Federated Learning (2); federated learning (2); Agent-Based Modelling (1); Clustering (1);
Main Referenced Unit & Research Centers
Interdisciplinary Centre for Security, Reliability and Trust (SnT) > FINATRAX - Digital Financial Services and Cross-organizational Digital Transformations (8)
ULHPC - University of Luxembourg: High Performance Computing (5)
Digital Society Initiative > University of Zurich (1)
Main Referenced Disciplines
Computer science (6)
Management information systems (5)
Engineering, computing & technology: Multidisciplinary, general & others (4)
Energy (2)
Finance (1)

Publications (total 8)

The most downloaded
385 downloads
Delgado Fernandez, J., Potenciano Menci, S., Lee, C. M., Rieger, A., & Fridgen, G. (15 November 2022). Privacy-preserving federated learning for residential short-term load forecasting. Applied Energy, 326. doi:10.1016/j.apenergy.2022.119915 https://hdl.handle.net/10993/52125

The most cited

21 citations (WOS)

Delgado Fernandez, J., Potenciano Menci, S., Lee, C. M., Rieger, A., & Fridgen, G. (15 November 2022). Privacy-preserving federated learning for residential short-term load forecasting. Applied Energy, 326. doi:10.1016/j.apenergy.2022.119915 https://hdl.handle.net/10993/52125

HORNEK, T., POTENCIANO MENCI, S., DELGADO FERNANDEZ, J., & PAVIĆ, I. (2024). Comparative Analysis of Baseline Models for Rolling Price Forecasts in the German Continuous Intraday Electricity Market. In Volume 38: Energy Transitions toward Carbon Neutrality: Part I. Stockholm, Sweden: Scanditale AB.
Peer reviewed

AMARD, A., DELGADO FERNANDEZ, J., BARBEREAU, T. J., FRIDGEN, G., & SEDLMEIR, J. (10 December 2023). Federated Learning in Migration Forecasting [Paper presentation]. ICIS 2023.
Editorial reviewed

DELGADO FERNANDEZ, J. (2023). Breaking data silos with Federated Learning [Doctoral thesis, Unilu - University of Luxembourg]. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/57042

Delgado Fernandez, J., Potenciano Menci, S., & Pavić, I. (2023). Towards a peer-to-peer residential short-term load forecasting with federated learning. In Proceedings of the 2023 IEEE Belgrade PowerTech (pp. 6). IEEE. doi:10.1109/PowerTech55446.2023.10202782
Peer reviewed

Sprenkamp, K., Delgado Fernandez, J., Eckhardt, S., & Zavolokina, L. (2023). Federated Learning as a Solution for Problems Related to Intergovernmental Data Sharing. In Proceedings of the 56th Hawaii International Conference on System Sciences (pp. 10).
Peer reviewed

Lee, C. M., Delgado Fernandez, J., Potenciano Menci, S., Rieger, A., & Fridgen, G. (03 January 2023). Federated Learning for Credit Risk Assessment [Paper presentation]. Proceedings of the 56th Hawaii International Conference on System Sciences, Maui, Hawaii, United States.
Peer reviewed

Delgado Fernandez, J., Potenciano Menci, S., Lee, C. M., Rieger, A., & Fridgen, G. (15 November 2022). Privacy-preserving federated learning for residential short-term load forecasting. Applied Energy, 326. doi:10.1016/j.apenergy.2022.119915
Peer Reviewed verified by ORBi

Delgado Fernandez, J., Barbereau, T. J., & Papageorgiou, O. (2022). Agent-based Model of Initial Token Allocations: Evaluating Wealth Concentration in Fair Launches. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/51934. doi:10.48550/arXiv.2208.10271

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