<Data Security>

1. Secure and federated genome-wide association studies for biobank-scale datasets, Nature Genetics, 2025
2. System and method for privacy-preserving distributed training of machine learning models on distributed datasets, US Patent 12,206,758 10, 2025
3. Veritas: Plaintext encoders for practical verifiable homomorphic encryption, Proceedings of the 2024 on ACM SIGSAC Conference on Computer and Communications, 2024
4. Pelta: shielding multiparty-FHE against malicious adversaries, Proceedings of the 2023 ACM SIGSAC Conference on Computer and Communications, 2023
5. Scalable and privacy-preserving federated principal component analysis, 2023 IEEE Symposium on Security and Privacy, 2023
6. An efficient threshold access-structure for RLWE-based multiparty homomorphic encryption, Journal of Cryptology, 2023
7. Privacy-Preserving Federated Recurrent Neural Networks, Proceedings on Privacy Enhancing Technologies (PoPETs), 2023
8. Privacy-preserving federated neural network learning for disease-associated cell classification, Patterns 2022
9. Bootstrapping for approximate homomorphic encryption with negligible failure-probability by using sparse-secret encapsulation, International Conference on Applied Cryptography and Network Security, 2022
10. Privacy-preserving and efficient verification of the outcome in genome-wide association studies, Proceedings on Privacy Enhancing Technologies, 2022
11. Truly privacy-preserving federated analytics for precision medicine with multiparty homomorphic encryption, Nature communications 2021
12. Revolutionizing medical data sharing using advanced privacy-enhancing technologies: technical, legal, and ethical synthesis, Journal of medical Internet research. 2021
13. POSEIDON: Privacy-preserving federated neural network learning, Network and Distributed Systems Security (NDSS) Symposium, 2021