collaborators

9 papers

q-bio.NC2026

Robust State-space Reconstruction of Brain Dynamics via Bootstrap Monte Carlo SSA

Sir-Lord Wiafe, Carter Hinsley, Vince D. Calhoun

Reconstructing latent state-space geometry from time series provides a powerful route to studying nonlinear dynamics across complex systems. Delay-coordinate embedding provides the…

eess.SP2026

Batch Effects In Brain Foundation Model Embeddings

Ye Tao, Bradley T. Baker, Yu Wu +4

Foundation models show strong potential for large-scale, high-dimensional biomedical applications, yet their ability to capture relevant neurobiological characteristics remains und…

cs.CV2026

Learning Structural-Functional Brain Representations through Multi-Scale Adaptive Graph Attention for Cognitive Insight

Badhan Mazumder, Sir-Lord Wiafe, Aline Kotoski +2

Understanding how brain structure and function interact is key to explaining intelligence yet modeling them jointly is challenging as the structural and functional connectome captu…

cs.CV2026

NeuroBRIDGE: Behavior-Conditioned Koopman Dynamics with Riemannian Alignment for Early Substance Use Initiation Prediction from Longitudinal Functional Connectome

Badhan Mazumder, Sir-Lord Wiafe, Vince D. Calhoun +1

Early identification of adolescents at risk for substance use initiation (SUI) is vital yet difficult, as most predictors treat connectivity as static or cross-sectional and miss h…

q-fin.CP2026

Conditioning on a Volatility Proxy Compresses the Apparent Timescale of Collective Market Correlation

Yuda Bi, Vince D Calhoun

We address the attribution problem for apparent slow collective dynamics: is the observed persistence intrinsic, or inherited from a persistent driver? For the leading eigenvalue f…

cs.CE2026

Warp Quantification Analysis: A Framework For Path-based Signal Alignment Metrics

Sir-Lord Wiafe, Vince D. Calhoun

Dynamic time warping (DTW) is widely used to align time series evolving on mismatched timescales, yet most applications reduce alignment to a scalar distance. We introduce warp qua…