Qingyun (Qinnuo) Guo

Université Laval

Québec, Canada

I am a PhD student in Electrical Engineering at Université Laval, supervised by Prof. Hanqing Zhao and Prof. Clément Gosselin. My research focuses on parallel robots, safe and stable reinforcement learning, world models, and physical human–robot interaction.

I am particularly interested in developing learning-based robotic systems that can interact safely and compliantly with humans and complex environments.

Before joining Université Laval, I received my M.Sc. in Control, Robotics and Autonomous Systems from Aalto University, where I worked on learning-based event-triggered control, multi-agent reinforcement learning, and communication-efficient decision making.

Research Interests

Robotics
World Models
Reinforcement Learning
Safe and Stable Control
Physical Human–Robot Interaction
Multi-Agent Systems
Parallel and Compliant Robotics

news

Sep 01, 2026	I started my PhD in Electrical Engineering at Université Laval, working on robotics, safe and stable control, world models, and physical human–robot interaction.
Apr 13, 2026	Our paper “Individual Control Barrier Functions-Guided Diffusion Model for Safe Offline Multi-Agent Reinforcement Learning” was accepted to the 23rd IFAC World Congress 2026.
Apr 13, 2026	Our paper “Priority-Driven Control and Communication in Decentralized Multi-Agent Systems via Reinforcement Learning” was accepted to the 23rd IFAC World Congress 2026.

selected publications

IFAC WC

Priority-Driven Control and Communication in Decentralized Multi-Agent Systems via Reinforcement Learning

Qingyun Guo, Junyi Shi, Tomasz Piotr Kucner, and 1 more author

In 23rd IFAC World Congress, 2026

arXiv Bib HTML Website

@inproceedings{guo2026priority,
  title = {Priority-Driven Control and Communication in Decentralized Multi-Agent Systems via Reinforcement Learning},
  author = {Guo, Qingyun and Shi, Junyi and Kucner, Tomasz Piotr and Baumann, Dominik},
  booktitle = {23rd IFAC World Congress},
  year = {2026},
}

IFAC WC

Individual Control Barrier Functions-Guided Diffusion Model for Safe Offline Multi-Agent Reinforcement Learning

Qingyun Guo, Junyi Shi, Jianuo Huang, and 1 more author

In 23rd IFAC World Congress, 2026

arXiv Bib HTML

@inproceedings{guo2026individual,
  title = {Individual Control Barrier Functions-Guided Diffusion Model for Safe Offline Multi-Agent Reinforcement Learning},
  author = {Guo, Qingyun and Shi, Junyi and Huang, Jianuo and Shi, Tianyu},
  booktitle = {23rd IFAC World Congress},
  year = {2026},
}

IROS

Event-Triggered Maps of Dynamics: A Framework for Modeling Spatial Motion Patterns in Non-Stationary Environments

Junyi Shi, Qingyun Guo, and Tomasz Piotr Kucner

In 2025 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2025

DOI Bib HTML

@inproceedings{shi2025event,
  title = {Event-Triggered Maps of Dynamics: A Framework for Modeling Spatial Motion Patterns in Non-Stationary Environments},
  author = {Shi, Junyi and Guo, Qingyun and Kucner, Tomasz Piotr},
  booktitle = {2025 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
  pages = {12924--12931},
  year = {2025},
  publisher = {IEEE},
  doi = {10.1109/IROS60139.2025.11247709},
}