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

July 20, 2026

Federico and Alberto attended the 17th World Congress on Computational Mechanics (WCCM) in Munich, Germany. Congratulations to Federico on his first conference presentation, where he discussed recent work in collaboration with Irina Tezaur and Anthony Gruber (Sandia National Labs) on a variationally-consistent non-intrusive model reduction formulation for Hamiltonian systems.

July 1, 2026

Alberto joins the Mathematical Sciences department at New Jersey Institute of Technology on a 0% appointment.

June 2, 2026

Our paper Toward adaptive non-intrusive reduced-order models: design and challenges is now available in Structural and Multidisciplinary Optimization. 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 paper here.

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