Danilo De Lima
Scientist In Advanced Mathematical Methods For Data Analysis
Hamburg, Germany
Summary
👤
Senior🎓
Top SchoolDanilo De Lima is a physicist-turned-data scientist with 10+ years applying advanced statistical and machine learning methods to petabyte-scale experimental data, including flagship work at CERN and European XFEL. He builds automated analysis pipelines, uses Bayesian optimization and hierarchical models for detector tuning and predictive maintenance, and develops self-supervised image-clustering and computer-vision solutions for real-world instrumentation. His toolset spans C/C++, Python, Java, Spark and Azure, and he has deployed Bayesian neural networks and Monte Carlo techniques in both research and industry consulting for renewable energy and large-scale physics analyses. Experienced leading international teams and coordinating efforts across O(100) collaborators, he combines hands-on coding with scientific rigor from a PhD in Physics. Fluent in Portuguese, English and Spanish, with intermediate German, Italian and French, he is comfortable operating in multilingual, cross-disciplinary environments.
10 years of coding experience
2 years of employment as a software developer
B.Sc., Electrical and Electronics Engineering, B.Sc., Electrical and Electronics Engineering at Universidade Federal do Rio de JaneiroPh.D., Physics, Ph.D., Physics at University of Glasgow
English, Portuguese, Spanish, French, German, Italian
Github Skills (55)
unfold10
plaidml9
detector9
bayesian8
image-processing7
actor-critic6
differential-equations6
region6
stochastic-differential-equations6
statistics6
machine-learning6
python6
geometry6
proximal-policy-optimization5
partial-differential-equations5
Programming languages (4)
Github contributions (5)
daniloefl/textmining
Mar 2017 - Oct 2017
Contributions:74 commits, 60 pushes, 1 branch in 7 months
daniloefl/Unfolder
Apr 2017 - Apr 2018
Software which implements the Full Bayesian Unfolding method to unfold a reconstructed distribution using PyMC3.
Contributions:216 commits, 193 pushes, 1 branch in 1 year
pythonunfoldmethodpymc3bayesian
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