Software development

I have 10+ years of experience developing software (C++ and Python) for international research collaborations (ATLAS and Pierre Auger Observatory)

Technical skills

Software development:

Python for data modeling (Pandas and NumPy), data visualization (Matplotlib and Plotly), automated testing (Pytest) and machine learning and statistical methods (SciPy, statsmodel, Keras from tensorflow, Scikit-learn)
C++
Git [GitLab and GitHub] and Continuous Integration
Docker
Kubernetes [Kubeflow]
SQL
Jupyter notebook

Significant contributions to the xAODAnaHelpers framework (data-processing tool):
- This tool was successfully used to promptly inspect data from the 2022 ATLAS data-taking operations
Responsible for the development and maintenance of a tool used by hundreds of users in the ATLAS Collaboration to apply corrections to the data
Significant contributions to the real-time data-driven decision-making software deployed in the 2022 ATLAS data-taking operations:
- Algorithms, configuration, validation and monitoring
- Software used to clean the data and to identify patterns in the data
Contributed with 87 merged MRs to The ATLAS Experiment's main software repository
Software development for deriving calibrations
Software development for several data analyses:
- Data preparations and statistical analyses
- Continuous integration and testing for early detection of issues and bugs
Implementation and deployment of a neural network to improve ATLAS simulations:
- Improved previous estimation by up to 60%
- Using NumPy, Pandas and Keras from tensorflow
Training and hyperparameter optimization of an attention-based deep learning method:
- Improved performance by up to 50%
- Using Docker and Kubernetes (Kubeflow pipelines and Katib)