Open Science

I strongly believe sharing code, knowledge and data openly is a fundamental part of science, especially the computational sciences. I am involved in the development of many open source tools.

I am a BIDS, MNE, and Neurodata team member. I am also a member of the MNE-Python steering committee. Specifically, I am a core-contributor to the following software packages:

  • MNE-Python: THE Python software package for MEG, EEG and iEEG data analysis, of which I am a core-developer.
  • MNE-BIDS: A Python package for facilitating formatting and analysis with the Brain Imaging Data Structure (BIDS), which I am a core-team member for EEG and iEEG development.
  • MNE-Connectivity: A Python package for connectivity analysis using MNE.
  • MNE-HFO: A Python package for high-frequency oscillation (HFO) detection using MNE.
  • SPORF: A package for training sparse oblique random forests.

I have also contributed to: pyDMD, pybids, bids-validator, scikit-learn and mlxtend.

Recently (as of 2021), I am involved in an effort to add oblique trees to scikit-learn, which is tracked via this Github issue.

During my postdoc, I have become involved with Py-Why. It is an organization in collaboration with Amazon, Microsoft and IBM on causal inference in Python, covering the entire pipeline from causal discovery, identification, estimation and refutation. I contribute design, ideas and code.

Open Data

I have also contributed multiple BIDS-compliant datasets to, totaling 105 subjects across multiple publications. Here is a list of contributed datasets and datasets I have helped curate, or collaborated on.