I am a scientific Python developer and computational neuroscience researcher. I build tested research software for neurodata, time-series analysis, model evaluation, and reproducible scientific workflows.
I work on problems where numerical correctness, data provenance, validation, and clear reporting matter. My background includes EEG and sleep research, experimental design, statistics, and computational neuroscience.
I am available for remote scientific Python and research-software work, and for research software, research assistant, predoctoral, and PhD roles in Vienna.
- NeuroData Release Security Audit — a local, read-only tool for checking privacy-relevant metadata, archive structure, broken references, and scan integrity before neurodata release. Current prerelease:
v0.3.0b1. - Sleep-EEG staging evaluation — external evaluation of YASA across 20 Sleep-EDF recordings and 28,259 aligned epochs, with recording-level uncertainty and stage-specific error analysis. Current release:
v0.3.1· Zenodo DOI. - Dense-EEG stop-signal pipeline — traceable QC, event reconstruction, reviewed ICA, provenance, and synthetic benchmarking for 129-channel EEG. Current release:
v0.3.0.
Additional work includes tested neural-dynamics simulations and a privacy-safe OpenSesame visual-world demonstration.
I contribute focused fixes, tests, validation rules, and documentation to scientific Python and neuroinformatics projects. Selected merged contributions:
- HED and BIDS: a correctness-first benchmark for source-preserving sleep-annotation retrieval, schema checks for behavioural timing columns and BrainVision file triplets, and a PyBIDS indexing fix.
- Pynapple: IntervalSet support for event-triggered averages, fixes for ISI histograms with constant intervals and failed tutorial downloads.
- MNE ecosystem: CUDA-backed Hilbert transforms, EEGLAB import fixes, rest-epoch validation, decoding safeguards, and OpenBLAS thread-tuning documentation.
- SleepECG: validation and documentation for external actigraphy inputs, a searchback correction, and a CAP Sleep Database reader.
Open work includes lagged cross-correlation in Pynapple and parallel manual and automated sleep annotations in BIDS/HED. See my GitHub contribution history for the full list.
Python: NumPy, pandas, SciPy, pytest, GitHub Actions, numerical validation, model evaluation, and reproducible data pipelines.
Neuroinformatics: MNE, MATLAB/EEGLAB, BIDS/HED, EEG quality control, sleep staging, event reconstruction, provenance, and metadata review.