Jonathan Wenger
Postdoctoral Researcher at Columbia University
New York, New York, United States
Summary
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Rockstar🎓
Top SchoolJonathan Wenger is a postdoctoral researcher at Columbia University with eight years of experience pushing the foundations of deep learning through rigorous machine learning research. He completed a PhD at the University of Tübingen after research visits at Columbia and the Broad Institute, blending strong theoretical training in mathematics and engineering physics with practical exposure to cross-disciplinary biomedical and computational problems. His work bridges advanced theory and empirical deep learning, informed by internships and consulting roles in industry that sharpened his software and systems thinking. Based in New York, he brings a pragmatic curiosity—equally comfortable proving theorems as prototyping models—and a track record of collaborating across academia and industry to translate foundational insights into reproducible experiments.
8 years of coding experience
Doctor of Science, Computer Science, Doctor of Science, Computer Science at University of TübingenMaster of Science (M.Sc.), Mathematics, Master of Science (M.Sc.), Mathematics at Technical University MunichMaster of Science (M.Sc.), Engineering Physics, Master of Science (M.Sc.), Engineering Physics at KTH Royal Institute of Technology
English, German
Github Skills (61)
pytorch10
ssreflect10
numerical-integration10
python10
modular10
classification10
stochastic10
machine-learning10
manifold10
gaussian-processes10
parameter-estimation10
stochastic-processes10
calibration10
numerical-methods10
probabilistic10
Programming languages (5)
Github contributions (5)
JonathanWenger/pycalib
Sep 2019 - Feb 2022
Non-Parametric Probabilistic Calibration for Classification
Contributions:131 commits, 1 PR, 195 pushes in 2 years 4 months
parametricnon-parametricmachine-learningcalibrationprobabilistic
JonathanWenger/personal-website
Jul 2018 - Aug 2019
Contributions:172 pushes, 1 branch in 1 year 1 month
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