2023 - Research.com Mathematics in Austria Leader Award
2022 - Research.com Engineering and Technology in Austria Leader Award
2022 - Research.com Mathematics in Austria Leader Award
2017 - SIAM Fellow For contributions to inverse problems, approximation to infinite dimensional control systems, and computational methods.
His main research concerns Mathematical optimization, Optimal control, Mathematical analysis, Applied mathematics and Augmented Lagrangian method. His Mathematical optimization research includes themes of Discretization, Regularization and Newton's method. He interconnects Dual, Partial differential equation, Distributed parameter system, Active set strategy and Boundary in the investigation of issues within Optimal control.
His Mathematical analysis research is multidisciplinary, incorporating perspectives in Inverse and Pure mathematics. His Applied mathematics study combines topics from a wide range of disciplines, such as Dynamical systems theory, Control theory, Inverse problem, State and Iterative method. His Augmented Lagrangian method research integrates issues from Elliptic curve, Quadratic programming, Hilbert space and Convex optimization.
His primary scientific interests are in Optimal control, Applied mathematics, Mathematical analysis, Mathematical optimization and Nonlinear system. The Optimal control study combines topics in areas such as Discretization, State, Pointwise and Newton's method. In his research, Taylor series and Lyapunov function is intimately related to Bellman equation, which falls under the overarching field of Applied mathematics.
As part of his studies on Mathematical analysis, Karl Kunisch often connects relevant areas like Boundary. Karl Kunisch has included themes like Regularization, Numerical analysis and Class in his Mathematical optimization study. His Control theory study incorporates themes from Artificial neural network and Control.
Karl Kunisch spends much of his time researching Optimal control, Applied mathematics, Nonlinear system, Control theory and Bellman equation. His Optimal control research is under the purview of Mathematical optimization. His study in Applied mathematics is interdisciplinary in nature, drawing from both Riccati equation, Navier–Stokes equations, Optimization problem, Pointwise and Newton's method.
His biological study spans a wide range of topics, including Bounded function, Mathematical analysis, Hamilton–Jacobi equation and Finite element method. His research in the fields of Parabolic partial differential equation overlaps with other disciplines such as Slew rate and Waveform. His Bellman equation study also includes
Karl Kunisch mainly investigates Optimal control, Applied mathematics, Nonlinear system, Bellman equation and Control theory. His Optimal control study is related to the wider topic of Mathematical optimization. His Applied mathematics research is multidisciplinary, incorporating elements of Control system, Penalty method, Riccati equation, Theory of computation and Optimization problem.
His work carried out in the field of Nonlinear system brings together such families of science as Mathematical analysis and Hamilton–Jacobi equation. His studies in Mathematical analysis integrate themes in fields like Controllability and Trajectory. He works mostly in the field of Control theory, limiting it down to concerns involving Class and, occasionally, Steady state, Function space and Reaction–diffusion system.
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Total Generalized Variation
Kristian Bredies;Karl Kunisch;Thomas Pock.
Siam Journal on Imaging Sciences (2010)
The Primal-Dual Active Set Strategy as a Semismooth Newton Method
M. Hintermüller;K. Ito;K. Kunisch.
Siam Journal on Optimization (2002)
Estimation Techniques for Distributed Parameter Systems
Harvey Thomas Banks;K. Kunisch.
Galerkin Proper Orthogonal Decomposition Methods for a General Equation in Fluid Dynamics
K. Kunisch;S. Volkwein.
SIAM Journal on Numerical Analysis (2002)
Lagrange multiplier approach to variational problems and applications
Kazufumi Ito;Karl Kunisch.
Convergence rates for Tikhonov regularisation of non-linear ill-posed problems
H W Engl;K Kunisch;A Neubauer.
Inverse Problems (1989)
Galerkin proper orthogonal decomposition methods for parabolic problems
Karl Kunisch;Stefan Volkwein.
Numerische Mathematik (2001)
Control of the Burgers equation by a reduced-order approach using proper orthogonal decomposition
K. Kunisch;S. Volkwein.
Journal of Optimization Theory and Applications (1999)
Primal-Dual Strategy for Constrained Optimal Control Problems
Maïtine Bergounioux;Kazufumi Ito;Karl Kunisch.
Siam Journal on Control and Optimization (1999)
Augemented Lagrangian Techniques for Elliptic State Constrained Optimal Control Problems
Maitine Bergounioux;Karl Kunisch.
Siam Journal on Control and Optimization (1997)
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