Xiaoxi He
Papers
2
Total Citations
7
H-Index
2
About
Xiaoxi He is an emerging researcher at the intersection of real-time systems, robotics, and on-device deep learning, with a focus on making intelligent robots more capable of operating in complex, dynamic environments. His work addresses fundamental challenges in how robotic systems manage unpredictable computational demands — particularly when navigating environments filled with moving obstacles and mechanical elements. His 2023 paper "RED: A Systematic Real-Time Scheduling Approach for Robotic Environmental Dynamics" introduces a principled framework for adapting scheduling strategies to environment-induced dynamics, earning five citations in its debut year and signaling strong early interest from the robotics and real-time systems communities. Complementing this, his work on "MIMONet" pushes the frontier of on-device deep learning by enabling robots to simultaneously process multiple input modalities — such as image and audio — and produce multiple outputs, mirroring human perceptual capabilities. With two citations already accrued, MIMONet reflects a timely contribution to the growing field of efficient edge AI. Together, He's research lays important groundwork for the next generation of intelligent, resource-aware robotic systems.
Research Focus
Key Achievements
Top Papers
- 1
- 2MIMONet: Multi-Input Multi-Output On-Device Deep Learning2 citations · 2023