Richard Schoonhoven
Assistant Professor In Multimodal AI at Amsterdam UMC
Randstad, Netherlands
Summary
👤
Senior🎓
Top SchoolRichard Schoonhoven is an assistant professor and researcher blending mathematics, physics and computer science with 11 years of experience in high-performance computing, optimization and multimodal AI. His PhD work focuses on end-to-end optimization of high-throughput imaging pipelines—combining gradient-based and blind tuning, GPU auto-tuning, and state-of-the-art deep learning—to accelerate tomographic and synchrotron imaging. He has published practical advances in real-time segmentation, GPU kernel auto-tuning and energy-aware model-steered optimization, and maintains open-source tools for pruning (LEAN_CNN) and black-box discrete optimization (BlooPy). Equally comfortable in Python, C++, Rust and CUDA, he bridges theory and production by tuning hardware and software for peak performance. An avid competitive athlete, he brings the same discipline from international powerlifting to high-impact research collaborations at Amsterdam UMC and CWI.
11 years of coding experience
1 year of employment as a software developer
Master of Science (MSc), Mathematics, cum laude, Master of Science (MSc), Mathematics, cum laude at Utrecht UniversityIB English A-HL: Language & Literature, 6/7, IB English A-HL: Language & Literature, 6/7 at RSG Broklede
English, cuda c/c++, python, c++, c#, mathematica, rust, haskell, bash/shell
Github Skills (64)
python10
testing10
gpu10
tuner10
os-agnostic10
optimization10
ecosystem9
package-management9
auto-tuning9
linux9
machine-learning9
conda9
opencl9
deep-learning9
kernel9
Programming languages (4)
Github contributions (5)
schoonhovenrichard/BlooPy
Aug 2021 - Apr 2024
Contributions:5 releases, 2 PRs, 16 pushes in 2 years 8 months
schoonhovenrichard/GPU_benchmarking_paper
Aug 2021 - Mar 2022
Contributions:42 commits, 30 pushes, 1 branch in 7 months
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