Mauricio Santamaría
Lead Data Scientist
Berlin, Germany
Summary
🤩
Rockstar🎓
Top SchoolMauricio Santamaría is a Lead Data Scientist based in Berlin with 11 years of experience bridging academic research and production ML at omni:us. He holds a PhD in Computer Science and has a deep background in computer vision, pattern recognition and biometric systems from a long research tenure at Universitat Politècnica de València. At omni:us he progressed from scientific engineer to senior and now lead data scientist, shipping applied AI for insurance automation and mentoring teams. Mauricio is also an active open-source contributor to PyTorch Lightning, improving logging, evaluation and example workflows to make large-scale training and CLI-driven experiments more reproducible. He blends rigorous research instincts with pragmatic engineering, comfortable moving models from prototype to multi-GPU production. An often-overlooked strength is his cross-cultural academic-to-industry trajectory, enabling clear communication between research, product and engineering stakeholders.
11 years of coding experience
11 years of employment as a software developer
Engineer, Telecommunications, Engineer, Telecommunications at Universidad Santo TomásUniversitat Politècnica de València
Stackoverflow
11reputation
130reached
0answers
1question
Github Skills (14)
pytorch10
machine-learning10
pytorch-lightning10
deep-learning10
python10
ai10
data-science9
cli9
command-line9
command-line-interface9
documentation7
completablefuture6
multithreading6
java6
Programming languages (14)
Github contributions (5)
Lightning-AI/pytorch-lightning
Oct 2020 - Dec 2022
Pretrain, finetune ANY AI model of ANY size on 1 or 10,000+ GPUs with zero code changes.
Role in this project:
ML Engineer
ML EngineerContributions:272 reviews, 49 commits, 62 PRs in 2 years 2 months
Contributions summary:Mauricio contributed to the `pytorch-lightning` repository, which focuses on training and fine-tuning AI models. Their commits primarily involved modifications to the logging and evaluation procedures, specifically addressing issues related to step values within the validation step. Furthermore, the user added the LightningCLI in the example and documentation to simplify command-line training. The user also made adjustments to the backbone image classifier, improving the overall structure and usability of the example, while updating tests and documentation.
aipretrainpythondeep-learningartificial-intelligence
omni-us/pagexml
Jul 2016 - Aug 2022
Library in C++ and a python wrapper for dealing with Page XML files
Contributions:18 releases, 291 commits, 1 PR in 6 years 1 month
cpppythonxmlpagexmlannotation-processing
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