Research & Publications
My research focuses on reliable motor-imagery EEG decoding when data distributions change across sessions or participants. The work combines leakage-controlled evaluation, source-session organization, domain adaptation, drift diagnostics, and reproducible scientific software.
Accepted for Publication
Accepted for Publication · Frontiers in Human Neuroscience - Brain-Computer Interfaces
Accepted for publication, Aug 2026
A matched comparison of global and selective source-session strategies for within-subject, cross-session motor-imagery EEG transfer.
Recommended citation: Shen, Y., and Degras, D. A Confidence-Gated Source Selection Strategy for Cross-Session Transfer in Brain-Computer Interfaces. Frontiers in Human Neuroscience, Brain-Computer Interfaces. Accepted for publication, Aug 2026. Article 1895016. doi:10.3389/fnhum.2026.1895016.
Under Review
Under Review
Manuscript under review
Proposing a ‘Linear-First’ decision rule using Paired Non-Inferiority Tests (TOST) to balance decoding accuracy against computational cost.
Under Review
Manuscript under review
A geometric framework that diagnoses BCI performance degradation by separating signal drift into raw sensor variability and feature-space distortions.
Under Review
Manuscript under review (solo author)
A cross-participant study of MI-EEG system selection: single decoders, uncertainty-routed decoder pairs, and ensembles compared by final accuracy and execution cost, with calibration-based selection tested on held-out participants.
Dissertation and Working Papers
Ph.D. Dissertation · University of Massachusetts Boston
Ph.D. Dissertation, University of Massachusetts Boston (Aug 2026)
Reliable MI-EEG decoding as a sequence of representation, transfer, drift measurement, adaptation, and recalibration choices.
Manuscript in Preparation
Manuscript in preparation
A tensor-based statistical framework extending MCCA to high-dimensional datasets, preserving structural information in multi-view neuroimaging analysis.