Postdoctoral Researcher
CISPA Helmholtz Center for Information Security
raouf.kerkouche at cispa.de
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Teaching
Privacy-Aware Document Visual Question Answering
Rubèn Tito, Khanh Nguyen, Marlon Tobaben, Raouf Kerkouche, Mohamed Ali Souibgui, Kangsoo Jung, Joonas Jälkö, Vincent Poulain D’Andecy, Aurelie Joseph, Lei Kang, Ernest Valveny, Antti Honkela, Mario Fritz, Dimosthenis Karatzas. Proceedings of the 18th International Conference on Document Analysis and Recognition (ICDAR 2024) pdf code |
A Unified View of Differentially Private Deep Generative Modeling
Dingfan Chen, Raouf Kerkouche, Mario Fritz. Proceedings of Transactions on Machine Learning Research (TMLR 2024). [Survey Certification] |
Private and Collaborative Kaplan-Meier Estimators
Shadi Rahimian, Raouf Kerkouche, Mario Fritz. Proceedings of the 23nd Workshop on Privacy in the Electronic Society (WPES 2024), held in conjunction with CCS 2024 |
FedLAP-DP: Federated Learning by Sharing Differentially Private Loss Approximations
Hui-Po Wang, Dingfan Chen, Raouf Kerkouche, Mario Fritz. Proceedings of the 24th Privacy Enhancing Technologies Symposium (PETS 2024) pdf code |
Towards Biologically Plausible and Private Gene Expression Data Generation
Dingfan Chen, Marie Oestreich, Tejumade Afonja, Raouf Kerkouche, Matthias Becker, Mario Fritz. Proceedings of the 24th Privacy Enhancing Technologies Symposium (PETS 2024) pdf code |
Client-specific Property Inference against Secure Aggregation in Federated Learning
Raouf Kerkouche, Gergely Ács, Mario Fritz. Proceedings of the 22nd Workshop on Privacy in the Electronic Society (WPES 2023), held in conjunction with CCS 2023 pdf code |
Private Set Generation with Discriminative Information
Dingfan Chen, Raouf Kerkouche, Mario Fritz. Proceedings of the Thirty-Sixth Annual Conference on Neural Information Processing Systems (NeurIPS 2022) pdf code |
Practical Challenges in Differentially-Private Federated Survival Analysis of Medical Data
Shadi Rahimian, Raouf Kerkouche, Ina Kurth, Mario Fritz. Proceedings of the Conference on Health, Inference, and Learning (ACM CHIL 2022) |
Constrained Differentially Private Federated Learning for Low-bandwidth Devices
Raouf Kerkouche, Gergely Ács, Claude Castelluccia, Pierre Genevès Proceedings of the thirty-seventh conference on Uncertainty in Artificial Intelligence (UAI 2021) |
Compression Boosts Differentially Private Federated Learning
Raouf Kerkouche, Gergely Ács, Claude Castelluccia, Pierre Genevès Proceedings of the 6th IEEE European Symposium on Security and Privacy (IEEE EuroS&P 2021) |
Privacy-Preserving and Bandwidth-Efficient Federated Learning: An Application to In-Hospital Mortality Prediction
Raouf Kerkouche, Gergely Ács, Claude Castelluccia, Pierre Genevès Proceedings of the Conference on Health, Inference, and Learning (ACM CHIL 2021) pdf code |
Federated Learning in Adversarial Settings
Raouf Kerkouche, Gergely Ács, Claude Castelluccia arXiv 2020 |
PC Member (Conferences): | CCS 2025, AISTATS 2025, CCS 2024, AISTATS 2024, IEEE SaTML 2024, AISTATS 2023, IEEE SaTML 2023 |
PC Member (Workshops): | CCS AISec 2023, NeurIPS AFT 2023, NeurIPS AFCP 2022, AAAI PPAI 2022 |
Journals Reviewer: | Nature Medicine 2023, ACM TOPS 2022, ECML PKDD 2022 (journal track) |
External Reviewer: | ICLR 2025, IEEE EuroS&P 2021 |
Organized Competitions: | Privacy Preserving Federated Learning Document VQA (NeurIPS 2023 Competition) |