Signals, systems, and modeling
Mathematically grounded models for EEG, voltage imaging, and time-varying biological data.
I am Raul Valle, a University of Florida Ph.D. student in Electrical and Computer Engineering based in Gainesville, Florida. This is my official website for research in signal processing, time-series machine learning, neuroengineering, research software, and selected photography.
The core topics that define Raul Valle's work at UF.
Mathematically grounded models for EEG, voltage imaging, and time-varying biological data.
Tooling for repeatable experiments, diagnostics, plotting, and GPU-accelerated iteration.
Biosignal acquisition, dynamical systems, and deployable engineering work tied to real constraints.
Canonical static URLs for the research and engineering work most relevant to Raul Valle.
Pipeline that turns brain-wave recordings (EEG) into a small set of hidden time-series ‘states’ using a state-space model (Hierarchical Linear Dynamical System, HLDS), then evaluates those states for prediction and separability.
Pipeline for 2D voltage imaging videos that flags ‘events’ (fast, localized changes) using statistical detectors inspired by radar signal processing, producing maps and summaries for downstream analysis.
System that extracts structured nodes (claims, evidence, limitations, etc.) from papers and scores them to support literature review and comparison across a collection.
Ergo integrates biosignal hardware, feature extraction, and simulation to test how control systems move between stable and unstable regimes under cooperating vs. competing subjects and fatigue.
The highest-signal pages for papers, talks, videos, and UF coverage tied to Raul Valle.
Use the publications page to find the Plato's Cave arXiv preprint, the DSI symposium talk video, UF AI coverage, and official UF mentions collected on one page.
ORCID, Google Scholar, UF pages, GitHub, and LinkedIn now form the clearest public identity cluster for the University of Florida researcher Raul Valle.
A quick note on using HLDS and related models to capture structure in EEG, instead of treating everything as i.i.d. features.
Portrait and character photography lives here as a secondary portfolio surface alongside the research work.