Matthias Fey
Software Engineer at Kumo.AI
Dortmund, North Rhine-Westphalia, Germany
Summary
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Rockstar🎓
Top SchoolMatthias Fey is a software engineer and creator of PyG (PyTorch Geometric) with a PhD in computer science from TU Dortmund and ten years of experience in graph representation learning. As a founding engineer at Kumo.AI he bridges research and production, contributing both high-level GNN architectures and low-level C++/CUDA PyTorch extensions (pytorch_cluster, pytorch_scatter, pytorch_sparse) that enable large-scale graph workloads. His open-source work includes key integrations with OGB and ongoing stewardship of PyTorch Geometric, making complex graph ML accessible and performant. Based in Dortmund, he pairs rigorous academic training with practical optimization skills to deliver scalable, community-adopted graph ML tools.
10 years of coding experience
Technische Universität Dortmund
Github Skills (28)
algorithms10
pytorch10
graphneuralnetwork10
c-language10
python10
operation10
gnn10
testing10
tensorrt10
sparse-matrix10
machine-learning10
tensorflow10
autograd10
cuda10
rust10
Programming languages (11)
Github contributions (5)
pyg-team/pytorch_geometric
Oct 2017 - Jan 2023
Graph Neural Network Library for PyTorch
Role in this project:
Software Engineer
Software EngineerContributions:43 releases, 2086 reviews, 4945 commits in 5 years 4 months
Contributions summary:Matthias contributed to the PyTorch Geometric library, focusing on improvements and feature additions in graph neural network implementations. They fixed compatibility issues in the Planetoid datasets related to NumPy, added helper functions for module equivalence and invariance testing, and implemented edge weight support to the LightGCN model. Further contributions include updates to the batching tutorial with cleaner code and the addition of a test to verify the correctness of the ClusterLoader.
pytorchgraph-convolutional-networksgeometric-deep-learningdeep-learningneural-graph
rusty1s/pytorch_cluster
Jan 2018 - Jan 2023
PyTorch Extension Library of Optimized Graph Cluster Algorithms
Role in this project:Back-end Developer
Back-end DeveloperContributions:39 releases, 18 reviews, 548 commits in 5 years 1 month
Contributions summary:Matthias appears to be primarily involved in the development of the PyTorch extension library for optimized graph cluster algorithms. The commits demonstrate the creation of core functionality, including the implementation of a grid clustering algorithm, along with related dependencies. Their work focuses on building out core libraries, including creating C++ implementations to take advantage of CUDA.
pytorchgeometric-deep-learningcluster-algorithmsmachine-learninggraph-neural-networks
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