Kristijan Armeni
Independent Research Scientist at Validate Research
Washington, District of Columbia, United States
Summary
🤩
Rockstar🎓
Top SchoolKristijan Armeni is an independent research scientist and open-source developer with a decade of experience at the intersection of cognitive neuroscience, neuroimaging (MEG/EEG/iEEG), and language-model research. He combines hands-on research software engineering—contributions to high-profile projects like MNE-Python and FieldTrip—with AI interpretability work that links transformer representations to brain signals. Based in Washington, DC, he leads reproducible research initiatives and civic-tech tooling such as the CIB Mango Tree dashboard for detecting coordinated inauthentic behavior in social media. His background spans PhD-level neuroimaging methods, data pipeline engineering, and mentoring contributors, reflecting a rare mix of experimental rigor and production-oriented open-source maintenance. An often-overlooked strength is his experience automating evaluation suites for working memory in language models, which bridges cognitive theory and practical model testing.
10 years of coding experience
5 years of employment as a software developer
PhD cognitive neuroscience, PhD cognitive neuroscience at Radboud UniversityJohns Hopkins UniversityMaster of Arts - MA Translation studies, Master of Arts - MA Translation studies at University of Ljubljana
English, French, Slovenian
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (13)
neuroscience10
megaparsec10
matlab10
python10
neuroimaging10
data-analysis10
electrophysiology9
statistics8
data-processing8
bids7
analyse7
machine-learning7
time-frequency5
Programming languages (8)
Github contributions (5)
fieldtrip/fieldtrip
Sep 2017 - May 2020
The MATLAB toolbox for MEG, EEG and iEEG analysis
Role in this project:
Back-end Developer
Back-end DeveloperContributions:5 commits, 7 PRs, 6 comments in 2 years 8 months
Contributions summary:Kristijan primarily contributed to improving the core functionality of the MATLAB toolbox for MEG, EEG, and iEEG analysis. Their work involved adding options for data preprocessing, such as removing the mean and modifying the colorbar. They fixed bugs, ensuring that code handles different data configurations correctly. Moreover, they improved the data2bids file to correctly treat trl matrix, highlighting their focus on data processing and analysis within the neuroimaging domain.
brainneurosciencetime-frequencyfieldtripieeg
mne-tools/mne-python
Oct 2020 - Feb 2024
MNE: Magnetoencephalography (MEG) and Electroencephalography (EEG) in Python
Role in this project:Back-end Developer
Back-end DeveloperContributions:10 reviews, 7 PRs, 38 comments in 3 years 4 months
Contributions summary:Kristijan primarily contributed to the development and maintenance of the MNE-Python library, focusing on extending its functionality for reading and processing neural data from various sources. Their work included implementing support for reading Neuralynx data, addressing temporal discontinuities in Neuralynx files, and optimizing the reading process. Furthermore, the user improved the library by storing online filter frequencies and measurement dates from .ncs headers in the `RawNeuralynx.info`.
visualizationneuroimagingneurosciencepythonstatistics
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