Mark Wronkiewicz
Data Scientist
Los Angeles Metropolitan Area United States
Summary
👤
Senior🎓
Top SchoolMark Wronkiewicz is a data scientist with 12 years of experience applying classical, deep, and reinforcement learning to real-world problems, currently working at NASA JPL in the Los Angeles area. He holds a PhD in Neuroscience from the University of Washington where his thesis advanced brain-computer interfaces for people with brain damage, and he blends rigorous scientific inquiry with practical engineering. Mark has production ML deployment experience across TensorFlow, Keras, Kubernetes/KubeFlow, Docker, and cloud platforms, and is fluent in Python with additional C++, Matlab, and Java expertise. His background spans academic research and industry roles, including machine learning engineering at Development Seed and contributions to MNE-Python improving inverse operator and covariance handling for EEG/MEG workflows. Comfortable moving models from lab to scale, he’s particularly interested in humanitarian and development applications of ML. A detail often missed: his work touches both low-level scientific data integrity (saving and reconstructing neuroimaging outputs) and high-level system orchestration for deployment.
12 years of coding experience
6 years of employment as a software developer
Doctor of Philosophy (PhD) Neuroscience, Doctor of Philosophy (PhD) Neuroscience at University of WashingtonBS Bioengineering and Biomedical Engineering, BS Bioengineering and Biomedical Engineering at Washington University in St. Louis
Github Skills (2)
neuroscience10
python10
Programming languages (10)
Github contributions (5)
mne-tools/mne-python
Sep 2013 - May 2016
MNE: Magnetoencephalography (MEG) and Electroencephalography (EEG) in Python
Role in this project:
Back-end Developer
Back-end DeveloperContributions:193 commits, 18 PRs, 314 comments in 2 years 8 months
Contributions summary:Mark primarily focused on modifying core functionality related to the creation and writing of inverse operators within the MNE-Python library, as evidenced by the consistent modification of files relating to inverse functions and covariance matrices. Contributions included adding options to the write_cov function, updating the implementation to match the C version, and incorporating units for source information. These changes enhanced the library's ability to save and reconstruct data consistently, likely aiming to improve the compatibility of data generated from different versions and sources.
visualizationneuroimagingneurosciencepythonstatistics
developmentseed/ml-hv-grid-pub
Mar 2018 - May 2019
Contributions:14 commits, 10 pushes, 1 branch in 1 year 2 months
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.