Who is Bruno?
I am the 4-th-year Computer Science Ph.D. student at the Paris-Saclay University (France 🇫🇷) and Federal University of ABC (Brazil 🇧🇷), happily advised by Professors Sylvain Chevallier, Marie-Constance Corsi and Raphael Y. de Camargo.
Research Interests
My current research interests include Learning Representation from the time series (Decoding, Generating and Transferring knowledge), Brain-Computer Interfaces, Machine Learning for brain decoding, Benchmark, and Riemannian Geometry (mostly Symmetric Positive Definite Neural Networks - SPDNets).
Open Source Projects
I strongly advocate for open source for reproducible science and community-driven progress, while occasionally working with closed code. I lead the widely used Python libraries Braindecode and MOABB
, actively shaping standards and enabling EEG Decoding in both. I also collaborate with related open-source projects like MNE-Python, MONAI, MONAI Generative, SpeechBrain.
You can usually check my current work on GitHub:
Community Involvement
During my PhD, I collaborated with research groups across the US (San Diego, San Francisco, Washington), UK, Ireland, Germany, Italy, Netherlands, Canada (Waterloo, MILA), Brazil (Sao Paulo), and France, resulting in over 16 publications (full/short papers, reports, abstracts) covering diverse aspects of my doctoral research. My publications are available on Google Scholar. I particularly enjoyed the experience of collaborating on self-contained, code-oriented projects 🧠⚙️. For academic cooperation, please contact me via email or LinkedIn.
Regarding community engagement, I organized the Braindecode Code-Sprint during the European summer of 2023, co-organized the Designing Brain-Computer Interfaces from theory to real-life scenarios Workshop at Graz BCI 2024 Conference and I am currently leading the Special Session on Decoding the brain time series at IEEE International Workshop on Machine Learning for Signal Processing (MLSP) 2025.
I have served as a reviewer for machine learning conferences and journals, NeurIPS (x2), ICLR, ICML, NeuroImage, Imaging Neuroscience, Journal of Machine Learning Research (JMLR) and Learning from Time Series for Health Workshop@ICLR, ensuring reviews are within my area of expertise.