Virginia Tech® home

Modeling, Model Reduction, Control & Optimization

Research Advisors in Modeling, Model Reduction, Control & Optimization

  • Bio Item
    Nicole Abaid , bio

    Dr. Abaid's research focuses on networked dynamical systems. She studies diverse biological systems, ranging from animal groups to brain networks, to inspire novel results in mathematical modeling and control.

  • Bio Item
    Daniel Appelö , bio

    Professor Daniel Appelö is a numerical analyst with an interest in computational techniques for solving differential equations fast and accurately. He is excited about applications in acoustics, electromagnetics, fluids, and more recently in quantum computing.

  • Bio Item
    Christopher Beattie , bio

    The principal research interests of Professor Beattie are in the areas of scientific computing and large scale computational linear algebra, with an emphasis on iterative Krylov methods.

  • Bio Item
    Jeff Borggaard , bio

    Professor Borggaard studies the design and control of fluids. This includes computational fluid dynamics, control theory, optimization, sensitivity analysis, uncertainty quantification, and reduced-order models. In each case, the application of these research areas to partial differential equations that describe fluids are of interest.

  • Bio Item
    John Burns , bio

    Professor Burns' current research is focused on computational methods for modeling, control, estimation and optimization of complex systems where spatially distributed information is essential. This includes systems modeled by partial and delay differential equations. Recent applications include modeling and control of thermal fluids, design and thermal management systems and optimization of mobile sensor networks.

  • Bio Item
    Paul Cazeaux , bio

    Professor Cazeaux's research deals with multiscale phenomena in mathematical physics and biology, with recent applications in quantum chemistry and condensed matter physics (2D materials).

  • Bio Item
    Yingda Cheng , bio

    Professor Cheng's research areas are in scientific computing, applied mathematics and data-driven modeling and computation. She develops numerical methods for partial differential equations, particularly those in higher dimensional space. The application area of Professor Cheng's research includes fusion energy and semiconductor device modeling, to name a few.

  • Bio Item
    Lauren M. Childs , bio

    Professor Childs develops and analyzes mathematical and computational models to examine biologically-motivated questions.

  • Bio Item
    Stanca M. Ciupe , bio

    Dr. Ciupe's research interest is in the field of applied mathematics, specifically, systems of ordinary and delay differential equations and their application to biology and medicine.

  • Bio Item
    Eric de Sturler , bio

    Professor de Sturler's research focuses on numerical analysis for large-scale computational problems with an emphasis on fast solvers for linear and nonlinear systems, inverse problems and parameter estimation, optimization, and design, including iterative solvers and numerical linear algebra, randomization, stochastic methods, model reduction, and high performance computing with applications in computational mechanics, such structural optimization and computational fluid dynamics, tomography and image reconstruction, big data, computational physics, biology, and computer graphics.

  • Bio Item
    Mark Embree , bio

    CMDA Program Director Professor Embree studies numerical linear algebra and spectral theory, with particular interest in eigenvalue computations for nonsymmetric matrices and transient behavior of dynamical systems.

  • Bio Item
    Serkan Gugercin , bio

    Professor Gugercin studies computational mathematics, numerical analysis, and systems and control theory with a focus on data-driven modeling and model reduction of large-scale dynamical systems with applications to inverse problems, structural dynamics, material design, and flow control.

  • Bio Item
    Traian Iliescu , bio

    At the core of Professor Iliescu's research program is his vision of using both mathematics and computations to provide new knowledge on turbulent fluid flows dominated by coherent structures and create models with practical impact in engineering, climate modeling, and medicine. The ultimate goal of his research program is to transform turbulence modeling as we know it today and use mathematics, computations, physics, and data to discover general laws of turbulent fluid flows.

  • Bio Item
    Honghu Liu , bio

    Professor Liu's research focuses on the design of effective low-dimensional reduced models for nonlinear deterministic and stochastic PDEs as well as DDEs. Applications to classical and geophysical fluid dynamics are actively pursued. Particular problems that are addressed include bifurcation analysis, phase transition, surrogate systems for optimal control, and stochastic closures for turbulence.

  • Bio Item
    Agnieszka Miedlar , bio

    Professor Miedlar conducts research in numerical analysis and scientific computing, with a focus on iterative solvers for large-scale linear systems and eigenvalue problems, and adaptive finite element methods (AFEMs).

  • Bio Item
    Michael A. Robert , bio

    Professor Robert builds and analyzes mathematical models to study biological phenomena. He is particularly interested in developing and exploring models to better understand how ecological, meteorological, anthropogenic, and evolutionary processes impact the emergence, spread, and control of infectious diseases.

  • Bio Item
    Shu-Ming Sun , bio

    Professor Sun's research interests include the mathematical theory of fluid mechanics, the theory of partial differential equations, and applied nonlinear analysis.

  • Bio Item
    Steffen Werner , bio

    Professor Werner conducts research at the intersection of scientific computing and numerical linear algebra with particular focus on scientific machine learning, model order reduction, data-driven modeling, optimization and control of partial differential equations, matrix equations and mathematical software development.

  • Bio Item
    Lizette Zietsman , bio

    Professor Zietsman's research area covers the development and analysis of fundamental numerical algorithms arising in the study of stability, control and estimation of distributed parameter systems typical in structural control, fluid flow control, and thermal systems.

Researchers in Modeling, Model Reduction, Control & Optimization

  • Bio Item
    Andrea Carracedo Rodriguez , bio

    Dr. Carracedo Rodriguez conducts research in numerical analysis, with a focus on efficiently building approximations to dynamical systems from data or via model reduction.

  • Bio Item
    Jorge Reyes , bio

    Dr. Reyes' research involves the theoretical and computational study of fluid dynamics primarily based on the Navier-Stokes equations (NSE). These studies consist of the finite element analysis of numerical solutions for full-order models and the development of corresponding reduced order models (ROMs).

  • Bio Item
    Kyle Dahlin , bio

    Dr. Dahlin is an NSF MPS Ascending Postdoctoral Fellow who uses mathematical tools to answer questions in epidemiology and ecology, particularly those related to the transmission and control of mosquito-borne parasites in human and wildlife populations.

  • Bio Item
    Nilton Garcia Hilares , bio

    Dr. Hilares' research interests lie in computational and applied linear algebra.

  • Bio Item
    Petar Mlinarić , bio

    Dr. Mlinarić conducts research in the field of model order reduction, in particular, structure-preserving and optimal methods.

  • Bio Item
    Ping-Hsuan Tsai , bio

    I am a postdoctoral associate working on developing data-driven reduced-order models for turbulent heat transfer applications. Particularly, focusing on developing stabilization strategies and error indicators for turbulent flows to be used in engineering routine and design analysis. In addition to turbulent flows, plasma physics is another application that I have been working on recently.

  • Bio Item
    Shixu Meng , bio

    Dr. Meng is interested in numerical analysis, applied analysis, scientific computing and machine learning, with applications to solving PDEs and inverse problems.