Methods & Toolchain

Methods & Toolchain

Methods are presented here as reusable scientific capabilities rather than a static skills list.

R and reproducible reporting

Reusable analysis pipelines, dynamic reports, statistics, data checks, tables, and publication-ready scientific outputs.

Machine learning and clustering

Self-organizing maps, dimensionality reduction, random forests, variable importance, and interpretable subgroup discovery.

Data visualization

Interactive visualizations, dashboards, animated outputs, and scientific figures that make multidimensional results inspectable.

MATLAB, GUI, and app development

MathWorks MATLAB, graphical interfaces, and user-friendly tools that let collaborators analyze data without needing to write every line of code themselves.

High-throughput electrophysiology

Spike-train analytics, burst detection, functional connectivity, periodicity analysis, and MEA visualization.

Network and biomarker analytics

Integrating molecular, imaging, cognitive, behavioral, multi-omics, and clinical signals into interpretable systems.