2017 - SIAM Fellow For sustained innovation at the dynamical systems theory/applications interface; notably for advances in the use of Koopman operator theory.
2015 - Fellow of American Physical Society (APS) Citation For fundamental contributions to the theory of threedimensional chaotic advection, measures and control of mixing, and development of a spectral operator theory approach to decomposition of complex fluid flows
1999 - Fellow of Alfred P. Sloan Foundation
Igor Mezic mainly investigates Nonlinear system, Mathematical analysis, Classical mechanics, Dynamical systems theory and Ergodic theory. His Nonlinear system study combines topics in areas such as Operator, Computation, Stability and Complex dynamics. His Mathematical analysis study combines topics from a wide range of disciplines, such as Eigenfunction and Dynamic mode decomposition.
The various areas that Igor Mezic examines in his Classical mechanics study include Flow, Chaotic, Vortex, Fluid mechanics and Mixing. The concepts of his Dynamical systems theory study are interwoven with issues in State variable, Statistical physics and Model predictive control. His studies in Reynolds number integrate themes in fields like Micromixer, Mixing, Micromixing and Hagen–Poiseuille equation.
Igor Mezic mainly focuses on Mathematical analysis, Dynamical systems theory, Mechanics, Nonlinear system and Control theory. A large part of his Mathematical analysis studies is devoted to Ergodic theory. His studies deal with areas such as Statistical physics, State space, Eigenfunction and Attractor as well as Dynamical systems theory.
His Mechanics research is multidisciplinary, incorporating elements of Micromixer, Mixing and Classical mechanics. His Nonlinear system study integrates concerns from other disciplines, such as Operator and Applied mathematics. His work is dedicated to discovering how Applied mathematics, Dynamic mode decomposition are connected with Eigenvalues and eigenvectors and other disciplines.
Applied mathematics, Eigenfunction, Operator, Dynamical systems theory and Eigenvalues and eigenvectors are his primary areas of study. His research in Applied mathematics intersects with topics in Dynamical system, Nonlinear system, Invariant and Dynamic mode decomposition. His Nonlinear system study is associated with Control theory.
His Eigenfunction study which covers Spectrum that intersects with Operator and Random dynamical system. His biological study spans a wide range of topics, including Ergodic theory, Operator theory, Mathematical analysis, Attractor and State space. His study in Mathematical analysis is interdisciplinary in nature, drawing from both Flow, Vector field and Topological conjugacy.
His main research concerns Eigenfunction, Applied mathematics, Spectrum, Dynamic mode decomposition and Operator. He has included themes like Fixed point, Attractor and Linear subspace in his Eigenfunction study. The various areas that he examines in his Applied mathematics study include Phase, Limit cycle, Nonlinear system, Invariant and Trajectory.
His work deals with themes such as Subspace topology, Mathematical analysis, Data-driven, Matrix decomposition and Vector field, which intersect with Dynamic mode decomposition. His Operator research incorporates elements of Discrete mathematics, State space and Ergodic theory. The study incorporates disciplines such as Dynamical systems theory and Continuous spectrum in addition to State space.
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Chaotic Mixer for Microchannels
Abraham D. Stroock;Stephan K. W. Dertinger;Armand Ajdari;Igor Mezić.
Spectral analysis of nonlinear flows
Clarence Rowley;Igor Mezic;Shervin Bagheri;Philipp Schlatter.
Bulletin of the American Physical Society (2009)
Spectral Properties of Dynamical Systems, Model Reduction and Decompositions
Nonlinear Dynamics (2005)
Analysis of Fluid Flows via Spectral Properties of the Koopman Operator
Annual Review of Fluid Mechanics (2013)
Marko Budišić;Ryan M. Mohr;Igor Mezić.
arXiv: Dynamical Systems (2012)
Linear predictors for nonlinear dynamical systems: Koopman operator meets model predictive control
Milan Korda;Igor Mezić.
Comparison of systems with complex behavior
Igor Mezić;Andrzej Banaszuk.
Physica D: Nonlinear Phenomena (2004)
A methodology for meta-model based optimization in building energy models
Bryan Eisenhower;Zheng O’Neill;Satish Narayanan;Vladimir A. Fonoberov.
Energy and Buildings (2012)
Ergodic Theory, Dynamic Mode Decomposition, and Computation of Spectral Properties of the Koopman Operator
Hassan Arbabi;Igor Mezić.
Siam Journal on Applied Dynamical Systems (2017)
Uncertainty and sensitivity decomposition of building energy models
Bryan Eisenhower;Zheng O'Neill;Vladimir A. Fonoberov;Igor Mezić.
Journal of Building Performance Simulation (2012)
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