Yixiao Sun
Papers
1
Total Citations
7
H-Index
1
About
Yixiao Sun is a researcher at the forefront of trustworthy autonomy, whose work addresses the critical challenge of out-of-distribution (OOD) data in robotic systems. His key research areas span robust machine learning, system-level reliability, and the safe deployment of learned components in real-world robotics. Sun’s major contribution lies in providing a holistic, system-level perspective on OOD data—moving beyond isolated model performance to examine how distribution shifts cascade through the entire autonomy stack, from perception to control. His seminal 2022 paper, “A System-Level View on Out-of-Distribution Data in Robotics,” has already garnered 7 citations, establishing a foundational framework for diagnosing and mitigating OOD failures. By highlighting the interplay between learned modules and their operational environment, Sun has helped shift the conversation from merely improving model accuracy to ensuring end-to-end system robustness. His work is essential reading for students and researchers building reliable, learning-enabled robots, offering both a clear taxonomy of OOD challenges and practical pathways toward trustworthy deployment in unpredictable settings.
Research Focus
Key Achievements
Top Papers
- 1A System-Level View on Out-of-Distribution Data in Robotics7 citations · 2022