Hoeseok Yang

Santa Clara University

Papers

1

Total Citations

6

H-Index

1

About

Hoeseok Yang is a leading researcher at the intersection of robotics, machine learning, and autonomous systems. His work focuses on enabling robots to operate effectively in high-uncertainty, high-force environments, particularly in subterranean and granular media. Yang’s most notable contribution is the development of a machine learning-driven control strategy for a snake-like robot designed for burrowing—a domain traditionally challenging due to unpredictable soil dynamics and extreme forces. By replacing complex physical models with data-driven approaches, his 2024 paper on this topic has already garnered 6 citations, signaling strong early impact and relevance. This work exemplifies his broader research philosophy: leveraging machine learning to overcome the limitations of classical robotics in unstructured environments. Yang’s achievements are particularly significant for applications in search-and-rescue, planetary exploration, and underground infrastructure inspection. His innovative fusion of bio-inspired design and adaptive control continues to push the boundaries of what autonomous robots can achieve in the most demanding conditions, making him a rising figure in field robotics and intelligent systems.

Research Focus

Key Achievements

1
H-Index
1
Papers
6
Total Citations
6
Avg Citations/Paper
🏆 Most Cited Paper
Machine Learning-Driven Burrowing with a Snake-Like Robot
6 citations · 2024
📈 Most Prolific Year: 2024 (1 Papers)
🤝 Key Collaborators: 3
🏛 Institutions: Santa Clara University

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago