Ryan A. McCarthy
Papers
1
Total Citations
2
H-Index
1
About
Ryan A. McCarthy is a researcher at the forefront of applying machine learning to underwater acoustics, with a focus on enabling autonomous underwater vehicles (AUVs) to operate intelligently in complex marine environments. His key research areas include machine learning for acoustic propagation modeling, range-dependent bathymetry simulation, and sound-aware autonomous navigation. McCarthy’s major contribution lies in developing transmission loss simulations that account for the scattering and multipath effects caused by variable seafloor topography—critical for optimizing acoustic communication ranges in real-world undersea missions. His most-cited work, "Machine learning transmission loss simulations in complex undersea environments with range-dependent bathymetry" (2023, 2 citations), lays the groundwork for a "sound-aware framework" where AUVs can adapt their behavior based on real-time acoustic conditions. Though early in its citation impact, this work represents a significant step toward integrating environmental acoustics with autonomous decision-making. McCarthy’s research holds promise for advancing underwater robotics, naval operations, and ocean monitoring, bridging the gap between physical oceanography and intelligent systems.
Research Focus
Key Achievements
Top Papers
- 1