Martin Lazar
Visiting Scientist (August 15th. – August 15th, 2022)
Funded by AvH -Alexander von Humboldt Stiftung/Foundation
University of Dubrovnik
My research area covers several topics ranging from microanalysis via applied mathematics to geophysical fluid dynamics.
Currently, I focus mainly on control theory and, in particular, on parameter dependent problems. The research topics include: Control theory: Control of parameter dependent systems (greedy control, averaged control), optimal control of parabolic problems Microlocal analysis: PDEs and homogenisation, velocity averaging, microlocal defect functionals (1-scale H-measures, semiclassical measures, H-distributions) Geophysical fluid dynamics: analytical modelling in oceanography
You might like
Randomized time-splitting in linear-quadratic optimal control By Daniël Veldman Introduction Solving an optimal control problem for a large-scale dynamical system can be computationally demanding. This problem appears in numerous applications. One example is Model Predictive Control (MPC), which requires the solution of several optimal control […]
Felix Klein: A Legacy of Innovation in Mathematics and Education By Roberto Rodríguez del Río, Complutense University of Madrid | IES San Mateo, Madrid Felix Christian Klein lived in a period of history of science in which Mathematics were involved in a process of transformation, […]
Control of Advection-Diffusion Equations on Networks and Singular Limits By Jon Asier Bárcena-Petisco, Márcio Cavalcante, Giuseppe Maria Coclite, Nicola de Nitti and Enrique Zuazua Introduction In the past few decades, models based on partial differential equations have been very effective in tackling many problems dealing with […]
Probabilistic Constrained Optimization on Flow Networks By Michael Schuster Uncertainty often plays an important role in the context of flow problems. We analyze a stationary and a dynamic flow model with uncertain boundary data and we consider optimization problems with probabilistic constraints in this context. The […]
Perceptrons, Neural Networks and Dynamical Systems By Sergi Andreu // This post is last part of the “Deep Learning and Paradigms” post Binary classification with Neural Networks When dealing with data classification, it is very useful to just assign a color/shape to every label, and so be able to visualize […]
Deep Learning and Paradigms By Sergi Andreu // This post is the 2nd. part of the “Opening the black box of Deep Learning” post Deep Learning Now that we have some intuition about the data, it’s time to focus on how to approximate the functions that […]
