Frank Schlimbach
Principal Engineer at Intel Corporation
Ruhr Region Germany
Summary
🤩
Rockstar🎓
Top SchoolFrank Schlimbach is a Principal Engineer based in the Ruhr Region with 12+ years of experience building high-performance back-end systems and ML tooling at Intel. He combines deep academic training (PhD in Mathematics, Statistics & Computing) with pragmatic engineering, driving production-ready enhancements to projects like scikit-learn-intelex, SWIG, and LLVM’s MLIR mesh dialect. Frank’s work spans algorithm implementation, distributed computing, and compiler-level transformation—evident in contributions such as SAGA optimizer support, mesh sharding/halo handling and MPI lowering. He excels at untangling legacy code and improving performance through targeted refactors, caching, and code-generation efforts. Colleagues rely on him for both architectural direction and hands-on fixes that bridge research and production. His profile hints at a quiet specialization: applying formal math and compiler techniques to accelerate real-world ML and HPC workloads.
12 years of coding experience
22 years of employment as a software developer
Diplom Informatiker, Diplom Informatiker at Paderborn UniversityDiplom-Informatiker, Diplom-Informatiker at Universität Paderborn / University of PaderbornDoctor of Philosophy (Ph.D.), Mathematics, Statistics & Computing, Doctor of Philosophy (Ph.D.), Mathematics, Statistics & Computing at University of Greenwich
German, English
Stackoverflow
56reputation
467reached
4answers
1question
Github Skills (37)
algorithm10
algorithms10
c-language10
python10
template-metaprogramming10
llvm10
scikit10
mpi10
machine-learning10
machine-learning-algorithms10
mlr10
data-structure10
scikit-learn10
data-structures10
cprogramming-language10
Programming languages (8)
Github contributions (5)
uxlfoundation/scikit-learn-intelex
Jun 2018 - Oct 2019
Extension for Scikit-learn is a seamless way to speed up your Scikit-learn application
Role in this project:
Back-end Developer & ML Engineer
Back-end Developer & ML EngineerContributions:1 release, 5 reviews, 349 commits in 1 year 3 months
Contributions summary:Frank primarily focused on implementing and fixing issues related to the data analysis and machine learning aspects of the Intel(R) DAAL extension for Scikit-learn. Contributions included fixing path issues, eliminating dead code and implementing new machine learning algorithms such as k-means, as well as supporting distributed computing and adding support for the Stochastic Average Gradient Descent (SAGA) optimizer and other linear models. Additionally, the user worked on code generation to support DAAL algorithms.
pythonswrepoai-machine-learningdata-scienceintel
llvm/llvm-project
Dec 2023 - Apr 2025
The LLVM Project is a collection of modular and reusable compiler and toolchain technologies.
Role in this project:Back-end Developer
Back-end DeveloperContributions:121 reviews, 21 PRs, 3 pushes in 1 year 4 months
Contributions summary:Frank's contributions center around the MLIR (Multi-Level Intermediate Representation) dialect for mesh operations within the LLVM project. They primarily worked on enhancing the `mesh` dialect, modifying its internal structure by changing how sharding is represented and handled. This included adding shard-size control, enabling more flexible halo region handling during spmdization, and implementing the mesh lowering to MPI. The changes involve code modifications to the `MeshOps.cpp` file and associated header/extension files, specifically for defining and managing sharding and halo regions.
compilerstechnologiesclangsubmittoolchain
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