Jan Lenssen
Full Professor at Universität des Saarlandes
Ruhr Region Germany
Summary
🤩
Rockstar🎓
Top SchoolJan Lenssen is a Senior Researcher and Group Leader at the Max Planck Institute for Informatics and a Founding Engineer at Kumo.AI, with a decade of experience at the intersection of differentiable programming, machine learning, graphics, and vision. He holds a PhD from TU Dortmund and has a track record of translating research into practical tools, from GPU-accelerated visualizers for PyTorch Geometric to differentiable algorithms for 3D reconstruction at Reality Labs. Jan blends deep academic rigor with startup pragmatism, routinely shipping performant implementations while leading research teams. Based in the Ruhr region of Germany, he is comfortable moving between low-level GPU optimization and high-level model design, a combination that helps bridge the gap between novel ideas and production-ready systems.
10 years of coding experience
10 years of employment as a software developer
Dr.-Ing / PhD Computer Science, Dr.-Ing / PhD Computer Science at TU Dortmund University
Github Skills (12)
pytorch10
deep-learning10
graph-neural-network10
graph-convolutional-networks10
python9
cuda9
gpu-programming9
computer-vision8
geometric-deep-learning8
scikit-image6
scipy6
matplotlib6
Programming languages (4)
Github contributions (5)
pyg-team/pytorch_geometric
Oct 2017 - Mar 2018
Graph Neural Network Library for PyTorch
Role in this project:
ML Engineer
ML EngineerContributions:78 commits, 1 PR, 70 pushes in 4 months
Contributions summary:Jan primarily contributed to the development of a kernel visualizer, implementing functionality to visualize graph convolutional network kernels. They then refactored the kernel visualizer code to comply with coding standards and also integrated a GPU algorithm to accelerate the processing. The user's work is focused on enhancing the visualization capabilities of the library and optimizing its performance through GPU utilization.
graph-neural-networkpytorchgeometric-deep-learninggraph-neural-networksdeep-learning
nnaisense/pytorch_sym3eig
Jan 2020 - Jun 2022
Pytorch extension: Batch-wise eigencomputation for symmetric 3x3 matrices
Contributions:11 commits, 2 PRs, 9 pushes in 2 years 5 months
pytorch
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