Summary
Research scientist with 7+ years of experience working in international academic teams specializing in human neuroimaging data (MEG, EEG) and language models • 6+ years of experience leveraging artificial neural networks and machine learning in data curation and analysis • Taking big-picture questions and translating them into robust analysis pipelines • Designing concise data visualizations and reports that take into account uncertainty • Passionate about developing technology for public good and safe digital spaces
Skills
Data Science: Python, PyTorch, Scikit-Learn, Polars, Jupyter, MATLAB, Git/GitHub, bash, LaTeX, SQL, High-performance computing (HPC), experiment tracking (DVC, MLFlow), continuous integration (CircleCI) Languages: Slovenian (first language), English (fluent), French (fluent)
Experience
CIB Mango Tree • Washington, DC • Sep. 2024 - present
Leading implementation of an open source tool for researchers, journalists, and watchdogs studying inauthentic online campaigns
Data Scientist (Accepted Offer, On Hold) • National Institute of Mental Health, National Institutes of Health • Jan. 2025
Selected for a competitive data scientist position in neuroimaging (offer on hold due to hiring freeze/lack of funding)
Assistant Research Scientist • Department of Psychological and Brain Sciences, Johns Hopkins University • Feb. 2024 - Jan. 2025
Curated data, built regression models of intracranial EEG, contributed to open source tools • Analyzed internal representations of language models (AI interpretability research) • Lead a team of graduate students in computational neuroscience methods and research design
Visiting Researcher • Department of Knowledge Technologies, Ljubljana, Slovenia* • July 2022
Proposed project and obtained an international travel grant (Slovenian Research Agency) • Developed a pipeline testing retrieval capacities of language models across training and scale (14M to 12B parameters) • Wrote and published final report
Postdoctoral Fellow • Department of Psychological and Brain Sciences, Johns Hopkins University • Oct. 2020 - Feb. 2024
Developed pipelines for deep neural network (LSTM, transformers) training and analyses • Wrote and edited research reports • Presented findings at international meetings
PhD Candidate • Donders Institute for Brain, Cognition and Behaviour, Nijmegen, The Netherlands • Sep. 2016 - Sep. 2020
Built neural data analyses pipelines using the FieldTrip toolbox • Designed and curated a large-scale dataset of brain electrical activity • Organized and chaired monthly interdisciplinary seminar on AI, cognitive neuroscience, and philosophy
Education
PhD in Cognitive Neuroscience • Donders Graduate School for Cognitive Neuroscience, Radboud University, Nijmegen, The Netherlands • 2016 - 2021
MSc in Cognitive Neuroscience • Donders Graduate School for Cognitive Neuroscience, Radboud University, Nijmegen, The Netherlands • 2014 - 2016
MA in Translation Studies • Faculty of Arts, University of Ljubljana, Ljubljana, Slovenia • 2011 - 2014
Publications
• Kressin Palacios G, Li Z, Armeni K. Executable science: Research software engineering practices for replicating neuroscience findings. 2025. The 3rd ACM Conference on Reproducibility and Replicability.
• Armeni K, Pranjći M, Pollak S. Transformer verbatim in-context retrieval across time and scale. 2024. Conference on Computational Natural Language Learning. link
• Armeni K, Honey C, Linzen T. Characterizing verbatim short-term memory in neural language models. 2022. Conference on Computational Natural Language Learning 2022. link
• Heilbron M, Armeni K, Schoffelen JM, Hagoort P, de Lange F. 2022. A hierarchy of linguistic predictions during natural language comprehension. Proceedings of the National Academy of Sciences. link
• Armeni K, Güçlü U, Van Gerven M, Schoffelen JM. 2022. A 10-hour within-participant magnetoencephalography narrative dataset to test models of language comprehension. Scientific Data. link
• Armeni K, Brinkman L, Carlsson L, …, Zurita-Milla R. 2021. Towards wide-scale adoption of open science practices: The role of open science communities. Science and Public Policy. 48(5), 2021, 605–611. link
• Armeni K, Willems RM, van den Bosch A, and Schoffelen JM. 2019. Frequency-specific brain dynamics related to prediction during language comprehension. NeuroImage 198, 283–295. link
• Armeni K, Willems RM, and Frank SL. 2017. Probabilistic language models in cognitive neuroscience: Promises and pitfalls. Neuroscience & Biobehavioral Reviews 83, 579–588. link
Talks
• March 2025. Executable science: reproducing neuroscience analyses through collaborative open source tools and practices. Slides. GW Open Source Con.
• October 2021. Meta-research paves the way, open science communities walk the walk. Stanford METRICS Seminar. Recording
• November 2019. Collaborative version control with Git and GitHub. International Max Planck Research School. Recording
Service & Volunteering
DMV Research Software Engineer Group • Washington, DC • 2024 - present
Co-Organizer • Organizing learning and networking meetups to advocate for professional research software engineering in academia
Reviewing • Virtual • 2020 - present
Served as scientific reviewer for: Imaging Neuroscience, Nature Communications, Scientific Reports, Association of Computational Linguistics Rolling Review, Nature Neuroscience, Neurobiology Of Language, Science and Public Policy