Pedro De Gusmão
Lecturer (Assistant Professor) at University of Surrey
England, United Kingdom
Summary
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Rockstar🎓
Top SchoolPedro De Gusmão is a Lecturer (Assistant Professor) and experienced data scientist with 11 years of applied research and industry experience spanning computer vision, deep learning, and federated learning. He holds a PhD in Electrical, Electronics and Communications Engineering from Politecnico di Torino and has held research and teaching roles at Oxford, Cambridge and now the University of Surrey, bridging rigorous academic work with practical deployments. Proficient in Python, MATLAB, ROS, TensorFlow and PyTorch, he contributes to open-source federated AI tooling—adding tutorials, dependency upgrades and a FedAdagrad strategy to the popular Flower framework—demonstrating a penchant for making advanced research accessible and reproducible. Based in the UK, Pedro combines strong engineering discipline with a track record of translating complex vision models into usable systems, often focusing on reproducible experiments and end-to-end workflows that are not immediately visible from publications alone.
11 years of coding experience
7 years of employment as a software developer
Bachelor of Science, Telecommunication Engineering, Bachelor of Science, Telecommunication Engineering at USP - Universidade de São PauloMaster of Science (MS), Telecommunications Engineering, Master of Science (MS), Telecommunications Engineering at Alta Scuola PolitecnicaMaster's, Telecommunication Engineering, Master's, Telecommunication Engineering at Politecnico di Torino
English, Italian, Portuguese
Stackoverflow
185reputation
28kreached
1answer
5questions
Github Skills (23)
application-framework10
pytorch10
python10
app-framework10
machine-learning10
deep-learning10
federated-learning10
web-framework10
artificial-intelligence9
ai9
documentation9
tensorflow7
hyperlink6
ros6
dump6
Programming languages (8)
Github contributions (5)
adap/flower
Sep 2020 - Jan 2023
Flower: A Friendly Federated AI Framework
Role in this project:
Full-stack Developer
Full-stack DeveloperContributions:87 reviews, 172 commits, 73 PRs in 2 years 3 months
Contributions summary:Pedro contributed to the documentation and quickstart guide for the Flower framework. This involved creating a tutorial for training a Convolutional Neural Network on MNIST using Flower and PyTorch, including shell scripts and Python code snippets. The user also made updates to upgrade the project's dependencies. Additionally, the user implemented a FedAdagrad strategy and made changes to incorporate it.
federated-analyticsfederated-learning-frameworkmachine-learningkeras-federated-learningflower
Ryan0v0/flower-profiler
Aug 2022 - Jan 2023
Flower - A Friendly Federated Learning Framework
Contributions:5 PRs, 29 pushes, 1 branch in 5 months
federated-learning-frameworkmachine-learningflowerframework-learningfederated-learning
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