Vita Publications

The estimation of functional connectivity (FC) from fMRI BOLD signals is limited by the inability of standard correlation measures to resolve weak, non-stationary inter-network dynamics, while classical sampling operators remain confined to fixed, analytically pre-specified kernels that cannot adapt to the heterogeneous temporal signatures of distinct brain regions. To close this gap, this paper introduces the Kolmogorov–Arnold deep sampling networks (KAN-DSN), the first framework to embed learnable Kolmogorov–Arnold Network (KAN) kernels within a provably convergent multilayer Durrmeyer integral-synthesis operator. [...]

As we move towards the Exascale era, the computational cost of Direct Numerical Simulations (DNS) remains a primary bottleneck for high-fidelity fluid flow analysis. Large Eddy Simulations (LES) provide a more affordable alternative, but they inherently lack sub-grid scale (SGS) details required to precisely describe turbulence [...]

High-fidelity computational fluid dynamics (CFD) simulations of turbulent flows are increasingly vital for biomedical and engineering applications. While direct numerical simulation (DNS) resolves all relevant flow scales, its computational requirements are often prohibitive for biomedical applications. [...]