Spencer Teetaert
PHD Student at University of Toronto Institute for Aerospace Studies
Old Toronto, Ontario, Canada
Summary
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Rockstar🎓
Top SchoolSpencer Teetaert is a PhD student at the University of Toronto specializing in robotics and continuous state estimation, with seven years of hands-on experience across research, industry, and student-led engineering teams. He designs sensing and control systems—from a low-cost wide-FOV LiDAR for hobbyists to autonomous charging robots—and has applied sim-to-real pipelines for safe control in aerial systems. Spencer combines strong software skills (Python, C, growing C++, ROS, SLAM, PyTorch) with mechanical CAD and hardware experience, and has improved modularity in open-source PyBullet drone environments. As former president of the U of T Robotics Association, he scaled programs serving 150+ members while leading competition teams, demonstrating both technical depth and operational leadership. Outside the lab he balances technical curiosity with creative pursuits like piano and outdoor hikes, reflecting a practitioner who thrives at the intersection of sensing, learning, and real-world deployment.
7 years of coding experience
4 years of employment as a software developer
Doctor of Philosophy - PhD, Robotics, Doctor of Philosophy - PhD, Robotics at University of Toronto
Stackoverflow
11reputation
225reached
0answers
1question
Github Skills (9)
openai-gym10
pybullet10
python10
reinforcement-learning10
robotics9
gymnasium9
controlling8
multi-agent7
opencv6
Programming languages (6)
Github contributions (5)
utiasDSL/gym-pybullet-drones
Jun 2022 - Jun 2022
PyBullet Gymnasium environments for single and multi-agent reinforcement learning of quadcopter control
Role in this project:
Backend Developer
Backend DeveloperContributions:7 reviews, 31 commits, 3 pushes in 13 days
Contributions summary:Spencer primarily focused on refactoring the codebase and improving modularity by addressing circular import issues and removing unnecessary dependencies. They moved enums to a separate file and updated import statements across multiple files, including those related to multi-agent and single-agent environments, as well as example scripts. The changes demonstrate a strong understanding of the project structure and dependency management within the PyBullet-based reinforcement learning environment.
gym-environmentspybulletmahjonggymnasiummulti-agent
spencerteetaert/loin-feeder-robot
May 2020 - Jun 2020
Project to design the vision and control systems for an application in industrial robotics
Contributions:34 PRs, 151 pushes, 23 branches in 1 month
roboticsvisionindustrialcomputer-visionros
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