Anders Kaestner
University Lecturer at Paul Scherrer Institut
Zurich, Zurich, Switzerland
Summary
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Senior🎓
Top SchoolAnders Kaestner is a University Lecturer and beamline scientist with 13+ years of experience at ETH Zürich and the Paul Scherrer Institut, specializing in neutron imaging, tomography and high-performance image processing. He designs and optimizes algorithms and instrumentation for low-dose computed tomography, improving signal-to-noise through denoising filters and acquisition strategies that make challenging experiments feasible. Comfortable across Python, Linux, and Qt, he combines hands-on software development with operational responsibility for the cold neutron imaging beamline ICON and contributions to the Swiss Spallation Neutron Source. As an educator he teaches "Quantitative big imaging," translating microscopy- and tomography-scale data into robust statistical conclusions for students. His background in signal processing (PhD) and earlier work on CBCT algorithm integration gives him a rare blend of academic rigor and production-focused algorithm engineering.
13 years of coding experience
OsbecksgymnasietMSc, Computer Systems Engineering, MSc, Computer Systems Engineering at Halmstad UniversityPh.D., Electrical Engineering (Signal Processing), Ph.D., Electrical Engineering (Signal Processing) at Chalmers University of Technology
Swedish, English, German
Github Skills (23)
tomography10
image-processing10
imaging10
solve8
reproducible-science7
geometry7
python6
algorithm6
science5
image-quality5
dataframe5
open-science4
multidimensional-data4
jupyter-notebook3
react3
Programming languages (5)
Github contributions (5)
ImagingLectures/Quantitative-Big-Imaging-2021
Feb 2021 - Dec 2021
Lecture material for the Quantitative big imaging class of 2021
Contributions:41 PRs, 313 pushes, 1 branch in 10 months
imaging
ImagingLectures/MNT_Lectures
Nov 2017 - Dec 2018
Lecture notes and Exercises for lecture 1
Contributions:29 commits, 1 PR, 24 pushes in 1 year 1 month
notes
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