Pedro Fernandez
Principal Technical Data Scientist Manager
Recife, Pernambuco, Brazil
Summary
👤
Senior🎓
Top SchoolPedro Fernandez is a Principal Technical Data Scientist Manager based in Recife with a decade of experience blending deep learning research and software engineering in industry and academia. He holds a PhD in Computer Science and completed postdoctoral work at Centro de Informática UFPE, bringing rigorous research methods to production ML systems. At CESAR he progressed from senior software and technical management roles to lead data science initiatives, pairing team leadership with hands-on model and pipeline development. His background includes research positions and lecturing, giving him strength in mentoring and translating complex ML concepts to practitioners. An active contributor to ML tooling, he has enhanced projects that programmatically visualize neural architectures, reflecting a practical interest in model transparency and reproducible design.
10 years of coding experience
15 years of employment as a software developer
Postdoctoral Fellow, Postdoctoral Fellow at Centro de Informática UFPEPhd. Computer Science deep learning and machine learnig, Phd. Computer Science deep learning and machine learnig at Universidade Federal de PernambucoMaster's degree Computer Science, Master's degree Computer Science at Universidad de Oriente. Cuba
Spanish, English, Portuguese
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (3)
deep-neural-networks10
latex10
python10
Programming languages (6)
Github contributions (5)
HarisIqbal88/PlotNeuralNet
Jan 2019 - Feb 2019
Latex code for making neural networks diagrams
Role in this project:
ML Engineer
ML EngineerContributions:6 commits, 1 PR in 1 day
Contributions summary:Pedro contributed to the development of a LaTeX-based neural network diagram generator. The commits primarily involve creating Python interfaces and defining functions to create and arrange blocks of neural networks using TikZ. The contributions include defining various layer types, connections, and implementing the ability to input external images. The user's work allows for the programmatic creation and visualization of complex neural network architectures.
diagramsdeep-neural-networkslatexneural-networks
pedrodiamel/pytorch-classification
Aug 2018 - Apr 2020
Pytorch model for classification
Contributions:60 commits, 5 PRs, 50 pushes in 1 year 8 months
cifar10cifar100classificationdeep-learningmnist
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