Lingyu Sun
Papers
1
Total Citations
3
H-Index
1
About
Lingyu Sun is an emerging researcher working at the intersection of autonomous systems, deep learning acceleration, and edge computing. Their most notable work focuses on autonomous micromobility systems (AMS) — a rapidly evolving domain encompassing low-speed minicabs, delivery robots, and similar intelligent platforms. In their standout 2024 paper, *A²: Towards Accelerator Level Parallelism for Autonomous Micromobility Systems*, Sun tackles a critical challenge in deploying multiple deep neural networks simultaneously across heterogeneous AI accelerators. By advancing the concept of Accelerator Level Parallelism (ALP), this research proposes a holistic framework for managing diverse accelerator resources more efficiently — a contribution with meaningful implications for real-world autonomous deployment at the edge. The work has already attracted early citation interest, reflecting its relevance to a community eager for practical solutions in on-device AI inference. Though early in their career, Sun's research addresses a timely bottleneck in the autonomy pipeline, bridging systems architecture and machine learning to push the boundaries of what resource-constrained autonomous platforms can achieve. Their trajectory suggests a promising voice in next-generation intelligent transportation and robotics research.
Research Focus
Key Achievements
Top Papers
- 1