Sandra Amador
Papers
1
Total Citations
7
H-Index
1
About
Sandra Amador is a leading voice in the emerging field of Industry 5.0, where her work bridges the gap between advanced artificial intelligence and human-centric manufacturing. Her primary research focuses on federated learning—a privacy-preserving machine learning paradigm—and its transformative applications in smart industrial ecosystems. Amador’s most influential contribution is her comprehensive 2023 state-of-the-art review, which systematically maps how federated learning can enable collaborative, decentralized intelligence across factories while safeguarding sensitive production data. This seminal paper, already garnering 7 citations in its first year, has become a foundational reference for researchers exploring the intersection of AI and sustainable, resilient manufacturing. Beyond this review, Amador is recognized for her innovative frameworks that integrate edge computing with federated architectures, addressing critical challenges in latency and data heterogeneity. Her work not only advances technical frontiers but also emphasizes ethical AI deployment, aligning with Industry 5.0’s core values of human well-being and environmental sustainability. As a rising scholar, Amador’s research is shaping the next generation of smart factories—where machines and humans collaborate seamlessly, and data privacy is paramount.
Research Focus
Key Achievements
Top Papers
- 1Federated Learning for Industry 5.0: A State-of-the-Art Review7 citations · 2023