Guillaume Witz is an image processing specialist and data scientist with over a decade of experience turning complex bioimages into quantitative insight for research groups at the University of Bern and beyond. Trained as a physicist (EPFL) and seasoned by hands-on microbiology and microscopy work at Harvard and Biozentrum, he uniquely bridges wet-lab experiments, microfluidics, and advanced image analysis pipelines. He develops reproducible Python tools and Fiji/Imaris automations that scale from Jupyter notebooks to cloud and cluster environments (SwitchEngine, AWS, GCE) and applies classical image processing alongside deep learning for enhancement and segmentation. A passionate educator, he creates openly available courses and code to help scientists adopt these methods. Less obvious: his background in AFM and polymer physics gives him an unusual perspective on image signal origins and noise, improving downstream analysis robustness.
Contributions:24 PRs, 175 pushes, 9 branches in 1 year 9 months
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