Pierre Schumacher
Research Engineer at Stealth Robotics Startup
Cambridge, Massachusetts, United States
Summary
🤩
Rockstar🎓
Top SchoolPierre Schumacher is a research engineer focused on reinforcement learning and muscle-driven robotic systems, with nine years of experience spanning academic and industry settings. After a satisfying PhD split between the Max Planck Institute and clinical brain research, and a visiting scholar stint at CMU, he transitioned to applied ML in fast-paced startups to bridge foundational science and production-ready AI. He has built large-scale ML pipelines, trained agents for human movement modeling, and now applies RL and deep learning to advance robotic manipulation at a stealth robotics company in Cambridge, MA. Known for combining rigorous physics and computational science training with hands-on engineering, he brings a rare blend of biomechanics intuition and practical deployment experience. An unspoken strength is his consistent movement between theory and practice—turning complex, muscle-driven models from lab prototypes into scalable systems.
9 years of coding experience
2 years of employment as a software developer
Bachelor of Science - BS, Physics, Bachelor of Science - BS, Physics at University of LuxembourgMaster's degree, Computational Science, Master's degree, Computational Science at Goethe University FrankfurtBachelor of Science - BS, Physics, Bachelor of Science - BS, Physics at Universite de LorraineBachelor of Science - BS, Physics, Bachelor of Science - BS, Physics at Universität des Saarlandes
Luxembourgish, English, French, German
Github Skills (41)
simulation10
physics-engine10
deterministic10
robotics10
simulator10
openai-gym10
dynamics10
bullet-physics10
mechanics10
api10
physics10
robot-simulator10
robotics-simulation10
mujoco10
reinforcement-learning9
Programming languages (2)
Github contributions (5)
P-Schumacher/Multiagent-Pong
Jun 2019 - Mar 2020
Contributions:41 commits, 2 PRs, 26 pushes in 9 months
P-Schumacher/myosuite
May 2023 - Sep 2024
MyoSuite is a collection of environments/tasks to be solved by musculoskeletal models simulated with the MuJoCo physics engine and wrapped in the OpenAI gym API.
Contributions:64 pushes, 16 branches in 1 year 4 months
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