Welcome!

Welcome to our website! We are a computational research group within the Newark College of Engineering at New Jersey Institute of Technology. Our mission is to enable computer-aided engineering design and analysis of real-world physical systems through the development of efficient computational models. We work on advancing the state of the art in reduced-order modeling for high-dimensional dynamical systems by combining equation-based and data-driven approaches to construct models that capture the essential physics while significantly reducing computational cost. This effort involves exploiting the structure of the governing equations when available, and developing novel learning-based methods when data serve as the primary source of information. Applications of interest include fluid flows in high- and low-speed aerodynamics, as well as systems in thermochemical non-equilibrium kinetics.


Alberto Padovan

News

February 11, 2026

Our preprint Toward Adaptive Non-Intrusive Reduced-Order Models: Design and Challenges is now available on arXiv. This work was done in collaboration with Prof. Karthik Duraisamy at the University of Michigan and his PhD student Amirpasha Hedayat. You can find the preprint here.

January 15, 2026

Our paper Petrov–Galerkin model reduction for collisional–radiative argon plasma was selected as Editor's Pick in Physics of Plasmas. Congratulations to Dr. Ivan Zanardi (formerly University of Illinois Urbana-Champaign, currently at PhysicsX) for the great work! You can find the paper here.

November 22, 2025

We attended the annual APS DFD conference in Houston, TX.

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