Yitong Sun
Papers
1
Total Citations
5
H-Index
1
About
Yitong Sun is a researcher at the forefront of integrating artificial intelligence, robotics, and high-fidelity simulation for disaster response. Their key research areas include earthquake simulation, virtual environment development, and material calibration for realistic physics-based modeling. Sun’s major contribution lies in bridging the gap between real-world disaster dynamics and virtual training systems, enabling AI-driven search and rescue robots to learn in immersive, physically accurate environments. Their most-cited work, "Executing realistic earthquake simulations in unreal engine with material calibration" (2024, 5 citations), demonstrates a novel approach to calibrating material properties within Unreal Engine to produce lifelike earthquake scenarios. This work is critical for training autonomous systems to navigate complex, post-disaster terrains without risking human lives. Though early in its citation impact, the paper addresses a pressing societal need—improving disaster preparedness through scalable, safe, and repeatable simulation. Sun’s research is notable for its interdisciplinary fusion of geophysics, computer graphics, and robotics, offering a practical pathway to enhance the resilience of AI-assisted emergency response. Their contributions are poised to influence both academic simulation research and real-world deployment of rescue robots.
Research Focus
Key Achievements
Top Papers
- 1