Hello team,
I am Susani and I am very interested and excited in contributing to MNE-Python for GSOC 2026.My ongoing journey into Machine Leaning is what sparked my fascination with how ML and Healthcare intersects.My goal is to use my background to make neurophysiological data accessible and interactive for health-tech community.
Technical Profile:
I have experience with React and building interactive components for data-heavy application, and I am eager to apply this to Documentation Interactivity goal.I also have a strong command of Python, using NumPy and Pandas for data manipulation and Matplotlib for creating high-quality scientific visualization.I have a background in C++ and data structures, which gives me solid foundation for efficient data handling.
Project Interest:
I am particularly interested in Project 4(Documentation Interactivity) and Jupyterlite Integration and I am excited to bridge the gap between static tutorials ad live, browser based environments where researchers can manipulate parameters and see results real time and I believe that my experience with state management and interactive component design will help me do that.
I have successfully set up my mne-dev environment and my sys_info is below:
Platform macOS-26.3-arm64-arm-64bit
Python 3.11.14 (main, Oct 21 2025, 18:27:30) [Clang 20.1.8 ]
Executable /opt/anaconda3/envs/mne-dev/bin/python
CPU Apple M4 (10 cores)
Memory 16.0 GiB
Core
├☑ mne 1.11.0 (latest release)
├☑ numpy 2.4.2 (unknown linalg bindings)
├☑ scipy 1.17.1
``└☑ matplotlib 3.10.8 (backend=macosx)
I am currently deep diving into mne.viz and mne.io to understand how MNE handles real-time plotting and data structures.
Best regards,
Susani,