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@adam2392

Adam Li

adam2392
United States

Currently, I am a Postdoctoral Research Scientist at Columbia University in the Causal Artificial Intelligence Lab, directed by Dr. Elias Bareinboim. I am an NSF-funded Computing Innovation Research Fellow. I did my PhD in biomedical engineering, specializing in computational neuroscience and machine learning at Johns Hopkins University. I worked with Dr. Sridevi V. Sarma in the Neuromedical Control Systems group. I also jointly obtained a MS in Applied Mathematics and Statistics with a focus in statistical learning theory, optimization and matrix analysis. I was fortunate to be a NSF-GRFP fellow, Whitaker International Fellow, Chateaubriand Fellow and ARCS Chapter Scholar during my time at JHU.

My research interests are broadly in the intersection areas of neuroscience, statistical machine learning, causal inference, control theory and dynamical systems. I am also extremely passionate about open-source everything.

I would use sponsorships to continue work on my open source software work summarized below.

Open Source Contributions Summary

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.
  • Scikit-tree: A Python package for scikit-learn compatible decision tree models.
  • PyWhy: I am a member of the PyWhy development team, an organization dedicated to open-source causal inference in Python, specifically leading development of pywhy-graphs, dodiscover and pywhy-stats.
  • PyData/Sparse: I am a developer sponsored by Google Summer of Code 2023 for the Sparse package, developing C++ code to develop a robust numpy-like API for sparse ndarrays.

Featured work

  1. mne-tools/mne-python

    MNE: Magnetoencephalography (MEG) and Electroencephalography (EEG) in Python

    Python 2,577
  2. py-why/dodiscover

    [Experimental] Global causal discovery algorithms

    Python 68
  3. neurodata/scikit-tree

    Scikit-learn compatible decision trees beyond those offered in scikit-learn

    Jupyter Notebook 55
  4. mne-tools/mne-bids

    MNE-BIDS is a Python package that allows you to read and write BIDS-compatible datasets with the help of MNE-Python.

    Python 123
  5. mne-tools/mne-connectivity

    Connectivity algorithms that leverage the MNE-Python API.

    Python 62
  6. mne-tools/mne-icalabel

    Automatic labeling of ICA components in Python.

    Python 86

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