I'm a machine learning scientist and engineer with over 10 years of experience and a deep passion for ML package development. I enjoy breaking down complex problems into manageable components, crafting simple and interpretable solutions, and implementing them with clean, modular code. I'm a strong believer in open-source software and always eager to contribute to projects that align with these values.
Note
I am on the lookout for new opportunities! Don’t hesitate to get in touch with me here on LinkedIn if you’re interested in connecting.
- I work across a broad range of data science tasks and specialize in time series problems such as forecasting, anomaly detection, motif discovery and classification.
- I lead data science projects built on Kedro, using it to enhance structure, maintainability, and team collaboration. I highly recommend the Kedro community—I've learned so much from it and contribute back whenever I can.
- I have worked on several packages that extend or integrate with the scikit-learn API, though most remain closed source.
- My academic and technical background spans engineering, applied mathematics, physics, and high-performance computing.
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kedro-dagster
A plugin for orchestrating Kedro pipelines using Dagster, a modern, asset-oriented orchestrator. -
giotto-tda
Created during my postdoc at EPFL, this is an open-source Topological Data Analysis library for feature engineering and unsupervised learning, built on top of scikit-learn. -
metaLBM
Developed during my PhD, this is a GPU-accelerated C++ simulation package for turbulence modeling using MPI, OpenMP, and CUDA.