
Mo Chen
Principal Investigator, MARS Lab
Associate Professor, SFU CS
CIFAR AI Chair, Amii Fellow
Office: TASC 1 8225
Email: mochen [at] cs [dot] sfu [dot] ca
Dr. Mo Chen is an Associate Professor in the School of Computing Science at Simon Fraser University, Burnaby, BC, Canada, where he directs the Multi-Agent Robotic Systems Lab. He holds a Canada CIFAR AI Chair position and is an Amii Fellow. Dr. Chen completed his PhD in the Electrical Engineering and Computer Sciences Department at the University of California, Berkeley in 2017, and received his BASc in Engineering Physics from the University of British Columbia in 2011. From 2017 to 2018, He was a postdoctoral researcher in the Aeronautics and Astronautics Department in Stanford University. Dr. Chen’s research interests include multi-agent systems, safety-critical systems, human-robot interactions, control theory, reinforcement learning, and their intersections.
PhD Students

robotic safety, numerical methods, multi-agent systems
also part of Computer Architecture Lab

reinforcement learning, safe learning, control theory
Personal website

multi-agent systems, robotic safety, reinforcement learning
Personal website

reinforcement learning

generative models, affective computing
also part of Rosie Lab

robotic safety, control theory
Personal website

motion planning, control theory
Research Assistants

learning-based planning

motion planning

motion planning

motion planning

motion planning

learning-based planning
also part of Ke Li’s lab

learning-based planning
also part of Ke Li’s lab

multi-agent systems

motion planning, interpretable learning

motion planning, safe learning

motion planning, multi-agent systems, robot learning

human-robot interactions, control theory
Alumni
PhD

deep learning, human-robot interactions
also part of Rosie Lab
Next: RBC Borealis

deep learning, transportation systems, autonomous driving
Next: Amazon

deep learning, human-robot interactions, autonomous driving
Personal website

reinforcement learning, human-robot interactions
Personal website

reinforcement learning, optimal control

reinforcement learning, multi-agent systems
Next: Sanctuary AI

reinforcement learning, human-robot interactions
Next: Waymo
MSc

robotic safety, computer vision

representation learning, optimal control
Next: NTWIST

computer vision, 3D reconstruction
Next: S&P Global

human-robot interactions, computer vision
also part of Rosie Lab
Next: Blue Boat Data

reinforcement learning, multi-agent systems

optimal control, reinforcement learning
Next: Ocado

optimal control, multi-agent systems
Next: Teck

optimal control, computer vision
Next: PhD at Princeton
Research Assistants

human-robot interactions

robotics

human-robot interactions

safe learning

reinforcement learning, multi-agent systems

machine learning, maritime applications

reinforcement learning

robotics


human-robot interactions
Next: Google

robotic safety

computer vision

reinforcement learning, optimal control

computer vision

software engineering, optimal control
Next: Amazon