Andrea Pierré
PHD Student at University of Massachusetts Lowell
Boston, Massachusetts, United States
Summary
👤
Senior🎓
Top SchoolAndrea Pierré is a PhD student and self-taught software engineer with 11 years of multidisciplinary experience bridging mechanical engineering, neuroscience research software, and production web platforms. Based in Boston, he has built reinforcement learning models and tooling for calcium imaging labs at Brown, contributed NWB support to Suite2p, and improved reproducibility with CI, linting, and containerized workflows. An active open-source contributor, Andrea has enhanced widely used projects like matplotlib and Hypothesis and added front- and back-end features to the LessPass password manager. His work blends deep learning (PyTorch/Julia), DevOps automation, and practical data engineering—an unusual combination rooted in hands-on lab software that enables experimental science to scale.
11 years of coding experience
13 years of employment as a software developer
Master's degree, Mechanical Engineering - minor: Mechatronics, Master's degree, Mechanical Engineering - minor: Mechatronics at UTBMLicence 2, Mechanical Sciences, Licence 2, Mechanical Sciences at Pierre and Marie Curie University
English, Italian, French, German, Chinese
Github Skills (36)
property-based-testing10
javascript10
python10
matplotlib10
testing10
plot10
numpy10
neuroscience10
latex10
password-manager10
front-end-development10
precommit10
vue10
pre-commit-hook10
1password10
Programming languages (21)
Github contributions (5)
MouseLand/suite2p
Sep 2020 - Aug 2022
cell detection in calcium imaging recordings
Role in this project:
Data Scientist
Data ScientistContributions:19 commits, 3 PRs, 18 comments in 1 year 11 months
Contributions summary:Andrea primarily focused on extending the `suite2p` codebase to support saving and loading data in the NWB format, specifically for calcium imaging recordings. Their contributions involved modifying existing code and adding new functionality for integrating with the NWB standard, including saving and loading fluorescence data, cell probabilities, and ROI information. Furthermore, the user wrote tests to ensure the correct saving and loading of data, demonstrating a focus on data integrity and compatibility with the NWB ecosystem. The user’s work directly supports the project’s goal of cell detection in calcium imaging recordings and data analysis.
imagingneurosciencedata-analysis
Farama-Foundation/PettingZoo
May 2022 - Aug 2022
A standard API for multi-agent reinforcement learning environments, with popular reference environments and related utilities
Role in this project:DevOps Engineer & Python Developer
DevOps Engineer & Python DeveloperContributions:13 reviews, 36 commits, 3 PRs in 3 months
Contributions summary:Andrea primarily contributed to improving the repository's code quality and maintainability. This included fixing flake8 errors and addressing pre-commit pipeline issues across various files. Further, they worked on removing obsolete files like `release_test.sh` and `requirements.txt` while also adding `codespell` to the `pre-commit` configuration. This suggests a focus on automating the build process and codebase standards.
multi-agent-reinforcement-learningapigymnasiumreinforcement-learningmultiagent-reinforcement-learning
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.