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DELGADO FERNANDEZ Joaquin

ORCID
0000-0003-1326-6134
Main Referenced Co-authors
POTENCIANO MENCI, Sergio  (11)
BARBEREAU, Tom Josua  (3)
FRIDGEN, Gilbert  (3)
Eckhardt, Sven (2)
LEE, Chul Min  (2)
Main Referenced Keywords
artificial intelligence (4); federated learning (4); Computer Science - Artificial Intelligence (2); Computer Science - Learning (2); data sharing challenges (2);
Main Referenced Unit & Research Centers
Interdisciplinary Centre for Security, Reliability and Trust (SnT) > FINATRAX - Digital Financial Services and Cross-organizational Digital Transformations (18)
ULHPC - University of Luxembourg: High Performance Computing (7)
Digital Society Initiative > University of Zurich (1)
Main Referenced Disciplines
Computer science (14)
Management information systems (9)
Engineering, computing & technology: Multidisciplinary, general & others (9)
Energy (5)
Finance (1)

Publications (total 18)

The most downloaded
536 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

115 citations (OpenAlex)

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

SARTIPI, A., DELGADO FERNANDEZ, J., POTENCIANO MENCI, S., & MAGITTERI, A. (21 February 2025). Bridging Smart Meter Gaps: A Benchmark of Statistical, Machine Learning and Time Series Foundation Models for Data Imputation [Paper presentation]. PowerTech 2025, KIEL, Germany. doi:10.1109/PowerTech59965.2025.11180477
Peer reviewed

NGUYEN, Q. V., DELGADO FERNANDEZ, J., & POTENCIANO MENCI, S. (14 February 2025). Spatiotemporal Graph Neural Networks in short term load forecasting: Does adding Graph Structure in Consumption Data Improve Predictions? [Paper presentation]. PowerTech 2025, Kiel, Germany. doi:10.1109/PowerTech59965.2025.11180479
Peer reviewed

ABELLÁN ÁLVAREZ, I., DELGADO FERNANDEZ, J., & POTENCIANO MENCI, S. (2025). Privacy-preserving distributed clustering: A fully homomorphic encrypted approach for time series. Computers and Security, 157, 104579. doi:10.1016/j.cose.2025.104579
Peer Reviewed verified by ORBi

Radovanovic, D., DELGADO FERNANDEZ, J., Schirl, M., Eibl, G., Unterweger, A., & POTENCIANO MENCI, S. (2025). Inferring the Hidden: Privacy Risks of Microaggregation in Smart Meter Data [Paper presentation]. DACH+ Conference on Energy Informatics, Aachen, Germany.
Peer reviewed

DELGADO FERNANDEZ, J., POTENCIANO MENCI, S., & Magitteri, A. (2025). Forecasting Anonymized Electricity Load Profiles [Paper presentation]. PowerTech 2025, KIEL, Germany. doi:10.1109/PowerTech59965.2025.11180602
Peer reviewed

Barbereau, T., DELGADO FERNANDEZ, J., & POTENCIANO MENCI, S. (2025). The governance of federated learning: a decision framework for organisational archetypes. Data and Policy, 7. doi:10.1017/dap.2025.10020
Peer reviewed

Sündermann, J., DELGADO FERNANDEZ, J., Kellner, R., Doll, T., Froriep, U. P., & Bitsch, A. (2024). Medical device similarity analysis: a promising approach to medical device equivalence regulation. Expert Review of Medical Devices, 1 - 13. doi:10.1080/17434440.2024.2402027
Peer Reviewed verified by ORBi

DELGADO FERNANDEZ, J., BARBEREAU, T. J., & PAPAGEORGIOU, O. (2024). Agent-based Model of Initial Token Allocations: Simulating Distributions post Fair Launch. ACM Transactions on Management Information Systems. doi:10.1145/3649318
Peer reviewed

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. doi:10.46855/energy-proceedings-10885
Peer reviewed

Sprenkamp, K., DELGADO FERNANDEZ, J., Eckhardt, S., & Zavolokina, L. (2024). Overcoming intergovernmental data sharing challenges with federated learning. Data and Policy, 6 (27). doi:10.1017/dap.2024.19
Peer Reviewed verified by ORBi

NGUYEN, Q. V., POTENCIANO MENCI, S., & DELGADO FERNANDEZ, J. (2024). Literature review for large-scale load forecasting with large volume of smart-meter data [Paper presentation]. 16th International Conference on Applied Energy, Niigata, Japan.
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

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

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

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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