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.
9 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 (49)
pytorch10
python10
classification10
machine-learning10
gaussian-processes10
numerics10
numerical-methods10
gpu-acceleration10
parametrize9
gpu9
gmm9
deep-learning9
gpytorch9
numpy8
decorator8
Programming languages (6)
Github contributions (5)
JonathanWenger/pycalib
Sep 2019 - Feb 2022
Non-Parametric Calibration for Classification (AISTATS 2020)
Contributions:131 commits, 1 PR, 195 pushes in 2 years 4 months
classificationprobability-calibrationneural-networksmachine-learningaistats-2020
JonathanWenger/probabilistic-linear-solvers-for-ml
Oct 2020 - Jan 2023
Contributions:62 commits, 60 pushes, 1 branch in 2 years 3 months
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