Marco Pinto-Orellana
Assistant Professor, Rochester Institute of Technology
I’m a scientist working on brain signal analysis with AI and statistics. I build tools for processing time series, pattern discovery and causal analysis.
This site hosts my projects and technical writing about signal processing, type theory, neuroscience and statistics.
Recent posts
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Optimization models in Python with PuLP
Facility location, the p-median problem, the traveling salesman and vehicle routing, written as integer linear programs and solved in Python.
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Numerical Hell: When Cross-Language Code Breaks (Part 1)
The same FIR filter gives different coefficients, and different detections, in MATLAB, Octave, Python and R.
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EDF files' specification
A byte-by-byte tour of the EDF and EDF+ file formats for biomedical signals.
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Innocent P-hacking
Why p-values estimated with too few simulations can lead to contradictory conclusions.
Research highlights
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Spectral dependence
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COFRE: Complex narrow-bandpass filters for very-low-frequency tracking in tinnitus identification
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SCAU: Modeling spectral causality for multivariate time series with applications to electroencephalograms
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Dyadic Aggregated Autoregressive Model (DASAR) for Automatic Modulation Classification.
Selected publications
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(2023). Statistical Inference for Modulation Index in Phase-Amplitude Coupling.
Preprint arXiv:2310.05398
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(2022). Spectral dependence. Econometrics and Statistics.
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(2021). COFRE: Complex narrow-bandpass filters for very-low-frequency tracking in tinnitus identification.
Preprint arXiv:2105.13476 Abstract & BibTeX
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(2021). SCAU: Modeling spectral causality for multivariate time series with applications to electroencephalograms.
Preprint arXiv:2105.06418
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(2020). RITS: A Toolbox for Assessing Complex Interventions via Interrupted Time Series.. BMC Medical Research Methodology.
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(2020). Dyadic Aggregated Autoregressive Model (DASAR) for Automatic Modulation Classification.. IEEE Access.