Examining the annealing schedules for RNA design algorithm. - Halid Emre Erhan; Sinem Sav; Stas Kalashnikov; Herbert H. Tsang (CEC, 2016)

Investigation of Multi-Objective Optimization criteria for RNA design. - David J. D. Hampson; Sinem Sav; Herbert H. Tsang (SSCI, 2016)

SIMARD: A simulated annealing based RNA design algorithm with quality pre-selection strategies. - Sinem Sav; David J. D. Hampson; Herbert H. Tsang (SSCI, 2016)

POSEIDON: Privacy-Preserving Federated Neural Network Learning. - Sinem Sav; Apostolos Pyrgelis; Juan Ramón Troncoso-Pastoriza; David Froelicher; Jean-Philippe Bossuat; Joao Sa Sousa; Jean-Pierre Hubaux (NDSS, 2021)

Scalable Privacy-Preserving Distributed Learning. - David Froelicher; Juan Ramón Troncoso-Pastoriza; Apostolos Pyrgelis; Sinem Sav; Joao Sa Sousa; Jean-Philippe Bossuat; Jean-Pierre Hubaux (Proc. Priv. Enhancing Technol., 2021)

Privacy-preserving federated neural network learning for disease-associated cell classification. - Sinem Sav; Jean-Philippe Bossuat; Juan Ramón Troncoso-Pastoriza; Manfred Claassen; Jean-Pierre Hubaux (Patterns, 2022)

slytHErin: An Agile Framework for Encrypted Deep Neural Network Inference. - Francesco Intoci; Sinem Sav; Apostolos Pyrgelis; Jean-Philippe Bossuat; Juan Ramón Troncoso-Pastoriza; Jean-Pierre Hubaux (ACNS Workshops, 2023)

Privacy-Preserving Federated Recurrent Neural Networks. - Sinem Sav; Abdulrahman Diaa; Apostolos Pyrgelis; Jean-Philippe Bossuat; Jean-Pierre Hubaux (Proc. Priv. Enhancing Technol., 2023)

How to Privately Tune Hyperparameters in Federated Learning? Insights from a Benchmark Study. - Natalija Mitic; Apostolos Pyrgelis; Sinem Sav (CoRR, 2024)

CURE: Privacy-Preserving Split Learning Done Right. - Halil Ibrahim Kanpak; Aqsa Shabbir; Esra Genç; Alptekin Küpçü; Sinem Sav (CoRR, 2024)

Generated Data with Fake Privacy: Hidden Dangers of Fine-tuning Large Language Models on Generated Data. - Atilla Akkus; Mingjie Li 007; Junjie Chu 002; Michael Backes 001; Yang Zhang 016; Sinem Sav (CoRR, 2024)

Abstract: Client Security Alone Fails in Federated Learning - 2D and 3D Attack Insights. - Santhosh Parampottupadam; Ralf Floca; Dimitrios Bounias; Benjamin Hamm; Saikat Roy; Sinem Sav; Maximilian Zenk; Klaus H. Maier-Hein (Bildverarbeitung für die Medizin, 2025)

A Taxonomy of Attacks and Defenses in Split Learning. - Aqsa Shabbir; Halil Ibrahim Kanpak; Alptekin Küpçü; Sinem Sav (CoRR, 2025)

Inclusive, Differentially Private Federated Learning for Clinical Data. - Santhosh Parampottupadam; Melih Cosgun; Sarthak Pati; Maximilian Zenk; Saikat Roy; Dimitrios Bounias; Benjamin Hamm; Sinem Sav; Ralf Floca; Klaus H. Maier-Hein (CoRR, 2025)