Yannik Schaelte
Research Scientist at DeepL
Munich, Bavaria, Germany
Summary
👤
Senior🎓
Top SchoolYannik Schaelte is a research scientist and computational mathematician with eight years of experience building scalable methods that blend mechanistic modeling and machine learning to tackle biomedical and cross-disciplinary problems. Currently at DeepL, he applies his AI research background to practical language technology while previously leading a multi-scale modeling team at the University of Bonn and consulting on causal inference, forecasting, and NLP for industry clients. His PhD work produced efficient, scalable statistical inference toolboxes (pyABC, pyPESTO, PEtab, FitMultiCell, AMICI) that are actively used in the systems biology and modeling communities. Yannik combines rigorous mathematical training with hands-on software engineering, contributing open-source code and reproducible research practices across academia and industry. Notably, he has collaborated with top AI labs (Mila, Oxford) on generative and likelihood-free inference, reflecting a rare mix of theoretical depth and practical implementation. Located in Munich, he shares research updates on Google Scholar and maintains an active developer presence on GitHub.
8 years of coding experience
1 year of employment as a software developer
Abitur, Abitur at Gymnasium HeepenMaster of Science (M.Sc.) Mathematics, Master of Science (M.Sc.) Mathematics at Bielefeld UniversityDoctor of Philosophy - PhD Mathematics, Doctor of Philosophy - PhD Mathematics at Technical University of MunichMathematics, Mathematics at Stockholm University
English, German, Swedish, Spanish, French, Latin, lorm (tactile signaling)
Stackoverflow
36reputation
350reached
4answers
0questions
Github Skills (179)
ode10
python10
toolbox10
abc10
slideshow10
generative10
density-estimation10
noise10
bayesian-inference10
scientific-computing10
modelica10
optimization10
reveal-js10
slide10
pandas10
Programming languages (11)
Github contributions (5)
ICB-DCM/Study-DFO
Jan 2018 - Jan 2020
Evaluation of Derivative-Free Optimizers for Parameter Estimation in Systems Biology.
Contributions:2 releases, 133 commits, 1 PR in 1 year 11 months
sbmlsystems-biologybiologyevaluationparameter
yannikschaelte/HierOpt
Nov 2017 - Dec 2018
Contributions:95 commits, 77 pushes, 1 branch in 1 year
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