Primary Research Area
- Controls, Dynamical Systems and Estimation
- Ph.D., Duke University, Durham, North Carolina, 2012
- M.A.Sc., Carleton University, Ottawa, Canada, 2007
- B.A.Sc., Carleton University, Ottawa, Canada, 2004
- Assistant Professor, Department of Aerospace Engineering, University of Illinois at Urbana-Champaign, August 2015-present
- Faculty Affiliate, Computational Science and Engineering, University of Illinois at Urbana-Champaign, May 2015-present
- Adjunct Assistant Professor, Department of Mechanical Engineering and Materials Science, Duke University, July 2014-present
- Visiting Senior Researcher, Department of Fluids, Thermal and Combustion Science, French National Center for Scientific Research, May 2013
- Postdoctoral Research Fellow, Department of Aeronautics and Astronautics, Stanford University, September 2012-May 2015
- Research Associate, Department of Mechanical Engineering and Materials Science, Duke University, August 2012-September 2012
- Research Fellow, Center for Human Science, Chapel Hill, NC, September 2008-May 2010
- Research Assistant, Department of Mechanical Engineering and Materials Science, Duke University, September 2008-July 2012
- Research Assistant, Department of Mechanical and Aerospace Engineering, Carleton University, September 2005-August 2007
For more information
Other Professional Employment
- Engineer, GEDEX Inc., Mississauga, Canada, May 2002-September 2003
- Engineer, National Research Council (NRC), Ottawa, Canada, May 2001-September 2001
- Faculty Advisor, Student Aircraft Builders (SAB)
Computational models of high-dimensional systems arise in a rich variety of engineering and scientific contexts. For example, computational fluid dynamics (CFD) and finite element (FE) analysis have become indispensable tools for many engineering applications. Unfortunately, high-fidelity simulations are often computationally prohibitive for parametric and time-critical applications such as design, design optimization, control, and virtual testing. Moreover, even when adequate computational resources are available, simulations often provide too little understanding of the solutions they produce. There are significant scientific and engineering benefits in developing and studying low-dimensional representations of high-dimensional systems that retain physical fidelity while substantially reducing the size and cost of the computational model.
My research is focused on developing theoretical and computational tools for low-dimensional and low-rank models of multi-scale and multi-physics problems.
- Model order reduction
- Nonlinear Systems
- Fluid-Structure Interactions
- Machine Learning
- System Identification
- Computational Fluid Dynamics
- Archive: Computational Mechanics
- Archive: Structural Mechanics/Structural Dynamics
Selected Articles in Journals
- Balajewicz, M. & Toivanen, J. "Reduced order models for pricing European and American options under stochastic volatility and jump-diffusion models". Journal of Computational Science 20, 198-204 (2017).
- Ansell, P. & Balajewicz, M. "Separation of unsteady scales in a mixing layer using empirical mode decomposition". AIAA Journal 55, 419-434 (2017).
- Balajewicz, M., Tezaur, I. & Dowell, E. "Minimal subspace rotation on the Stiefel manifold for stabilization and enhancement of projection-based reduced-order models for the compressible Navier-Stokes equations". Journal of Computational Physics 321, 224-241 (2016).
- Balajewicz, M., Amsallem, D. & Farhat, C. "Projection-based model reduction for contact problems". International Journal for Numerical Methods in Engineering 106, 644-663 (2015).
- Balajewicz, M. & Farhat, C. "Reduction of nonlinear embedded boundary models for problems with evolving interfaces". Journal of Computational Physics 274, 489-504 (2014).
- Balajewicz, M., Dowell, E. & Noack, B. "Low-dimensional modeling of high-Reynolds-number shear flows incorporating constraints from the Navier-Stokes equation". Journal of Fluid Mechanics 729, 285-308 (2013).
- Cordier, L., Noack, B. R., Tissot, G., Lehnasch, G., Delville, J., Balajewicz, M., Daviller, G. & Niven, R. K. "Identification strategies for model-based control". Experiments in Fluids 54, 121 (2013).
- Balajewicz, M., & Dowell, E., "Reduced-order modeling of flutter and limit-cycle oscillations using the sparse Volterra series". Journal of Aircraft 49, 1803-1812 (2012).
- Balajewicz, M. & Dowell, E. "Stabilization of projection-based reduced-order models of the Navier-Stokes equations". Nonlinear Dynamics 70, 1619-1632 (2012).
- Balajewicz, M., Nitzsche, F. & Feszty, D. "Application of multi-input Volterra theory to nonlinear, multi-degree-of-freedom aerodynamic systems". AIAA Journal 48, 56-62 (2010).
- Nair, N., & Balajewicz, M. "Transported snapshot model order reduction approach for parametric, steady-state fluid flows containing parameter dependent shocks". Submitted for review (2017).
- I. Tezaur, J. Fike, K. Carlberg, M. Barone, D. Maddix, E. Mussoni, M. Balajewicz. "Advanced Fluid Reduced Order Models for Compressible Flow". Sandia Laboratories Report, Sand No. 2017-10335. Sandia National Laboratories, Albuquerque, NM (2017)
- I. Tezaur, J. Fike, K. Carlberg, M. Balajewicz, M. Barone, E. Mussoni. "Model Reduction for Compressible Cavity Simulations Towards Uncertainty Quantification of Structural Loading". Sandia Laboratories Report, Sand No. 2016-9463. Sandia National Laboratories, Albuquerque, NM (2016)
- List of Teachers Ranked as Excellent by their Students (Spring 2016, Fall 2016, Spring 2017)
- Illinois Collins Scholar (2016)
- Journal of Computational Science, ICCS 2016 Best Paper Award (2016)
- Natural Sciences and Engineering Research Council of Canada (NSERC) Postgraduate Fellowship (2010-2012)
- Center for Human Science Residential Fellowship (2008-2011)
- Canada-EU Student Exchange Program (CESAer) (2007)
- Carleton University Entrance Scholarship (2000)
- USNCCM12 Travel Award (2012)
- SIAM Travel Award (2012)