Neuroscience · signal analysis
NeuroAlpha
Extracting patterns from noisy neurophysiological signals, with signal methods and machine learning.
Problem
Neural signals arrive with noise, artifacts, and few labels. Without a clear pipeline, it is hard to move from a plot to a testable hypothesis.
Approach
We combine signal processing with models you can audit: filtering, features, and, when the data allows, networks built for time series.
Outcome
A research pipeline for neurophysiological signals. The value is the method and reproducibility, not an invented accuracy percentage.
Stack
Python · NumPy · scikit-learn · time series