4 citations · 4 across the 20 of their papers we have counts for
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Low-Cost High-Order Singular Value Decomposition for Tensor-Based Reconstruction from Sparse Sensor Measurements: Urban Flow and Air-Quality Applications
Arindam Sengupta, Paul Jeanney, Ricardo Vinuesa +2
Urban flow and air-quality simulations generate high-dimensional datasets describing velocity and pollutant transport across multiple spatial, temporal, and physical-variable dimen…
Reduced-order modeling of a viscoelastic turbulent jet with hybrid machine learning models
Christian Amor, Adrián Corrochano, Marco Edoardo Rosti +1
Adding flexible polymers to a Newtonian solvent confers complex properties to the resulting solution. The additional complexity substantially increases the computational cost of nu…
A temporal deep learning framework for calibration of low-cost air quality sensors
Arindam Sengupta, Tony Bush, Ben Marner +2
Low-cost air quality sensors (LCS) provide a practical alternative to expensive regulatory-grade instruments, making dense urban monitoring networks possible. Yet their adoption is…
Agentic Exploration of PDE Spaces using Latent Foundation Models for Parameterized Simulations
Abhijeet Vishwasrao, Francisco Giral, Mahmoud Golestanian +8
Flow physics and more broadly physical phenomena governed by partial differential equations (PDEs), are inherently continuous, high-dimensional and often chaotic in nature. Traditi…
CardioMOD-Net: A Modal Decomposition-Neural Network Framework for Diagnosis and Prognosis of HFpEF from Echocardiography Cine Loops
Andrés Bell-Navas, Jesús Garicano-Mena, Antonella Ausiello +3
Introduction: Heart failure with preserved ejection fraction (HFpEF) arises from diverse comorbidities and progresses through prolonged subclinical stages, making early diagnosis a…