Papers
2
Total Citations
12
H-Index
2
About
Federica Garin’s research lies at the intersection of distributed control, networked systems, and privacy-preserving computation. She is best known for pioneering work on source localization using Poisson integrals, a mathematically elegant approach that enables agents in a network to pinpoint the origin of a signal through local, iterative exchanges—a foundational contribution to distributed estimation. Her most cited paper on this topic (2012, 7 citations) has inspired further studies in sensor networks and robotics. Garin also made a significant impact with her distributed algorithm for computing network size without revealing individual node identities (2013, 5 citations). This work, which avoids leader selection and relies solely on local information, is a key step toward privacy-preserving coordination in multi-agent systems. Her methods, grounded in system identification, offer practical solutions for large-scale, decentralized networks where communication and trust are limited. Garin’s contributions are notable for their theoretical rigor and real-world applicability, making her a respected voice in the growing field of secure and scalable distributed control.
Research Focus
Key Achievements
Top Papers
- 1Source Localization Using Poisson Integrals7 citations · 2012
- 2