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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
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deep learning, transportation systems, autonomous driving
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deep learning, human-robot interactions
also part of Rosie Lab
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robotic safety, numerical methods, multi-agent systems
also part of Computer Architecture Lab
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reinforcement learning, safe learning, control theory
Personal website
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generative models, affective computing
also part of Rosie Lab
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multi-agent systems, robotic safety, reinforcement learning
Personal website
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reinforcement learning
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robotic safety, control theory
Personal website
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motion planning, control theory
Research Assistants
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learning-based planning
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motion planning
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motion planning
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motion planning
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motion planning
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learning-based planning
also part of Ke Li’s lab
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learning-based planning
also part of Ke Li’s lab
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multi-agent systems
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motion planning, interpretable learning
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motion planning, safe learning
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motion planning, multi-agent systems, robot learning
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human-robot interactions, control theory
Alumni
PhD
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deep learning, human-robot interactions, autonomous driving
Personal website
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reinforcement learning, human-robot interactions
Personal website
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reinforcement learning, optimal control
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reinforcement learning, multi-agent systems
Next: Sanctuary AI
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reinforcement learning, human-robot interactions
Next: Waymo
MSc
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robotic safety, computer vision
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representation learning, optimal control
Next: NTWIST
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computer vision, 3D reconstruction
Next: S&P Global
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human-robot interactions, computer vision
also part of Rosie Lab
Next: Blue Boat Data
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reinforcement learning, multi-agent systems
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optimal control, reinforcement learning
Next: Ocado
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optimal control, multi-agent systems
Next: Teck
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optimal control, computer vision
Next: PhD at Princeton
Research Assistants
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human-robot interactions
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robotics
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human-robot interactions
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safe learning
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reinforcement learning, multi-agent systems
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machine learning, maritime applications
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reinforcement learning
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robotics
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reinforcement learning, optimal control
Next: MSc at Carnegie Mellon University
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human-robot interactions
Next: Google
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robotic safety
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computer vision
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reinforcement learning, optimal control
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computer vision
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software engineering, optimal control
Next: Amazon