Erik Wijmans
Member Of Technical Staff at Thinking Machines Lab
San Francisco, California, United States
Summary
🤩
Rockstar🎓
Top SchoolErik Wijmans is a research-focused machine learning engineer with 11 years of experience building and scaling embodied AI and reinforcement learning systems, currently a Member of Technical Staff in the Bay Area. He holds a PhD in Computer Science from Georgia Tech and has applied his expertise at Apple, Facebook AI, Intel Labs, and Oculus, specializing in training agents in simulated worlds and transferring skills to the real world. Erik is an active open-source contributor to high-impact projects like Habitat-Sim/Habitat-Lab and Sample Factory, where his work on navigation, scene parsing, and RNN performance directly improved simulator fidelity and RL throughput. He also maintains a PyTorch PointNet2 implementation and optimized recurrent policies in popular RL repos, showing strength across both 3D perception and scalable RL training pipelines. Known for pragmatic engineering of core systems, he frequently navigates low-level performance fixes (e.g., PackedSequence, PathFinder) as well as higher-level research problems, bridging simulation and real-world deployment. Based in San Francisco, he blends deep academic training with hands-on systems engineering to push embodied intelligence toward practical applications.
11 years of coding experience
3 years of employment as a software developer
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at Georgia Institute of TechnologyBachelor's degree, Engineering Physics, Bachelor's degree, Engineering Physics at Juniata CollegeBachelor's degree, Computer Engineering, Bachelor's degree, Computer Engineering at Washington University in St. Louis
Github Skills (27)
pytorch10
ppp10
c-language10
gru10
python10
simulator10
machine-learning10
rnn-model10
recurrent-neural-networks10
n10
reinforcement-learning10
ml10
mle10
deeplearning-ai10
deep-learning10
Programming languages (6)
Github contributions (5)
erikwijmans/Pointnet2_PyTorch
Dec 2017 - Jul 2021
PyTorch implementation of Pointnet2/Pointnet++
Role in this project:
ML Engineer
ML EngineerContributions:1 release, 53 commits, 43 PRs in 3 years 7 months
Contributions summary:Erik primarily focused on implementing and refactoring code related to Pointnet2 and Pointnet++ models within a PyTorch environment. Their contributions involved modifying model architectures, specifically within the `Pointnet2SemSeg.py` and `Pointnet2Cls.py` files. These changes included adjustments to the layers and the overall structure of the models to improve performance and functionality.
pytorchpointnet2point-cloudpytorch-lightninghydra
facebookresearch/habitat-lab
Apr 2019 - Oct 2022
A modular high-level library to train embodied AI agents across a variety of tasks and environments.
Role in this project:Back-end Developer
Back-end DeveloperContributions:172 reviews, 194 commits, 146 PRs in 3 years 6 months
Contributions summary:Erik primarily focused on improving the Habitat-Lab simulator, specifically in areas related to compatibility with habitat-sim and improvements to agent functionality. This included addressing comments, fixing formatting, and updating quaternion usage. The user also implemented features related to object navigation tasks, adding fog-of-war to the topdown map and correcting the naming of pointgoal navigation sensors. These commits show the user working to improve core functionality of the simulator.
ai-agentaicomputer-visionroboticssimulator
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