Juan Ramón Troncoso-Pastoriza

This paper introduces SF-GWAS, a secure federated framework for GWAS that enables efficient and accurate analysis of private genomic data across institutions.

The paper introduces FAMHE, a privacy-preserving federated analytics system using multiparty homomorphic encryption, enabling accurate analysis of distributed medical data without sharing patient-level information.

This paper develops secure genotype imputation methods using homomorphic encryption, showing comparable accuracy and efficiency to non-secure methods while protecting genetic data privacy.

This paper presents a privacy-preserving framework for genomic data analysis using cryptography and blockchain, enabling secure and transparent data access for citizens.