Joseph Suprenant
Papers
1
Total Citations
4
H-Index
1
About
Joseph Suprenant is a researcher advancing the frontiers of autonomous networked robotic systems, with a primary focus on signal processing and direction-of-arrival (DoA) estimation for high-frequency communications. His key research areas encompass millimeter-wave and future terahertz (THz) band connectivity, particularly for ground, aerial, and space-based robotic platforms operating in real-time, autonomous environments. Suprenant’s most cited work, "Single-Sample Direction-of-Arrival Estimation by Hankel-matrix Decompositions" (2022, 4 citations), introduces a novel, computationally efficient method for rapidly estimating signal direction using minimal data—a critical capability for maintaining high data-rate links in dynamic, latency-sensitive scenarios. This contribution addresses a fundamental bottleneck in modern autonomous systems, where traditional multi-sample DoA techniques are too slow for agile platforms. While his citation count is still growing, the work’s immediate relevance to next-generation wireless networks and autonomous swarms highlights its potential impact. Suprenant’s research sits at the intersection of robotics, communications, and advanced signal processing, promising to enable more reliable, high-speed connectivity for the autonomous systems of tomorrow.
Research Focus
Key Achievements
Top Papers
- 1