Watch a 13-minute conference presentation from eSAAM 2023 exploring a novel Federated Learning Simulation Engine (FLSE) designed to facilitate privacy-preserving machine learning research. Learn how this scalable and portable tool enables researchers to validate federated learning models in production-like environments while maintaining hardware independence and model agnosticism. Discover how the simulation engine can be used both as a standalone application or integrated into larger architectures, providing concurrent testing capabilities and metric performance analysis. Presented by Borja Arroyo Galende from GATV UPM, this talk demonstrates how the FLSE supports the development of trustworthy and ethical AI by allowing thorough validation and verification of federated learning approaches before production deployment.