Sinem Sav
EPFL IC IINFCOM LDS
BC 249 (Bâtiment BC)
Station 14
CH-1015 Lausanne
Web site: Web site: https://lds.epfl.ch/
Fields of expertise
- Security & privacy
- Privacy-preserving machine learning
- Federated learning
- Applied crypto
- Privacy-preserving machine learning
- Federated learning
- Applied crypto
Biography
I am a 4th year PhD student under the supervision of Prof. Jean-Pierre Hubaux at the Laboratory for Data Security (LDS) at EPFL. I earned my MSc and BSc in Computer Science from Bilkent University.I am currently working on privacy-preserving federated learning by relying on multiparty homomorphic encryption. In particular, I apply crypto to neural networks to preserve the confidentiality of the data in the distributed setting.
Awards
Applied research competition in Europe
10-14 November 2021
"Homomorphic Encryption-based Secure Viral Strain Classification", Track II
30 October 2021
Publications
Selected publications
| Sinem Sav, Jean-Philippe Bossuat, Juan R. Troncoso-Pastoriza, Manfred Claassen, and Jean-Pierre Hubaux Patterns 3, 2022 |
Privacy-Preserving Federated Neural Network Learning for Disease-Associated Cell Classification |
| Sinem Sav, Apostolos Pyrgelis, Juan R. Troncoso-Pastoriza, David Froelicher, Jean-Philippe Bossuat, Joao Sa Sousa, Jean-Pierre Hubaux NDSS, 2021 |
POSEIDON: Privacy-Preserving Federated Neural Network Learning |
| David Froelicher, Juan R. Troncoso-Pastoriza, Apostolos Pyrgelis, Sinem Sav, Joao Sa Sousa, Jean-Philippe Bossuat, Jean-Pierre Hubaux PETS, 2021 |
Scalable Privacy-Preserving Distributed Learning |
Teaching & PhD
Teaching Assistance
I have also been involved as a teaching assistant for the following courses:- CS-523 Advanced topics on privacy enhancing technologies
- COM-402 Information Security and Privacy