Georgios I. Orfanidis
Papers
1
Total Citations
4
H-Index
1
About
Georgios I. Orfanidis is a researcher at the forefront of signal processing and autonomous networked systems, with a primary focus on direction-of-arrival (DoA) estimation for next-generation communication networks. His most cited work, "Single-Sample Direction-of-Arrival Estimation by Hankel-matrix Decompositions" (2022), introduces a groundbreaking method that enables rapid DoA estimation using only a single snapshot of data—a critical capability for modern robotic platforms operating in high-frequency bands like mm-wave and future THz. This innovation addresses the stringent latency and connectivity demands of autonomous ground, aerial, and space vehicles, allowing them to maintain high data-rate links in dynamic environments. By leveraging Hankel-matrix decompositions, Orfanidis’s approach significantly reduces computational complexity while preserving accuracy, marking a notable advancement over traditional multi-sample techniques. With 4 citations to date, this work has already captured attention in the signal processing community for its practical implications in 6G and beyond. Orfanidis’s contributions bridge theoretical elegance with real-world deployment challenges, positioning him as a rising voice in the intersection of array processing and autonomous systems.
Research Focus
Key Achievements
Top Papers
- 1