I'm working on geometric inverse problems. I studied line crack identification using the reciprocity gap principle and I'm working on interface identification using the level set method. Also, I worked on adaptive parameterization for parameter estimation (regularization by discretization).

- Inverse scattering for target identification in random media.
- Time reversal, secure communications in random media.
- Wave propagation in randomly inhomogeneous media.
- Analysis and computation of inverse problems such as electrical impedance tomography.
- Effective properties of high contrast composite materials.

My background is primarily in optimization, including interior point methods for linear and semidefinite programming. Although I continue to be interested in optimization for its own sake, I'm participating in this program at IPAM because of my interest in statistical issues and computational issues in applied inverse problems.

My primary background is numerical analysis and optimization, i am interested in computational methods for interface problems and pde-constrained optimization. Moreover, i am working on several applications of these techniques, e.g. to inverse problems in materials science and to semiconductor design.

I've worked on inverse problems in wave propagation and also on electrical impedance tomography. Currently I'm working on radar imaging problems.

I am interested in regularization methods for nonlinear inverse problems with emphasis on iterative regularization methods. Issues are convergence analysis, stopping rules and more numerical aspects. Applications we are interested in include parameter identification in pdes e.g. in connection with heat conduction problems. This is also a link to our industry-oriented projects, where we work mainly with steel and automotive industry, but also increasingly with financial institutions. More info: www.indmath.uni-linz.ac.at and the links mentioned there.

My research interests are in the theory of inverse problems with applications to linear systems arising in the discretization of ill-posed problems. In particular, they involve the analysis of noise filtering properties of iterative methods and their applications to signal and image processing.
Recently I deal with theoretical links between regularization and matrix algebra preconditioning, in order to identify classes of preconditioners which "simultaneously" give fast reconstruction and noise filtering. Special emphasis is given to the numerical approach for structured linear systems (Toeplitz, Hankel matrices).

My interests are in the inverse scattering theory, currently I'm working on the inverse scattering problem for 2-D wave equation in anisotropic media at fixed energy. My thesis advisors are Prof. Gregory Eskin and Prof. James Ralston; I'm in my last year of graduate studies, expected to receive my Ph.D. in Spring 2004.

I've investigated the training of neural networks which is a nonlinear and ill-posed parameter-identification problem and studied the effects of iterative regularization methods, applied to this process.

I've studied mathematics, physics (and some economics) at the university of linz, where I got my PhD this spring under the supervision of Heinz Engl. so far, I've mainly concentrated on theory and numerics of regularization methods for parameter identification problems in elliptic / parabolic pdes from interior or boundary measurements.

My interest has been in the area of ‘local’ regularization methods for inverse problems. The ideas of localization can lead to the possibility of applying differing amounts of regularization in different parts of the domain of the solution, as well as the ability to design more efficient solution methods for the problem.  To date these ideas have mostly been applied to linear Volterra and Fredholm integral equations, although the extension to nonlinear problems is of much current interest to me.

By training I'm a numerical analyst. My research interests are inverse problems in imaging, in particular X-ray CT, emission tomography, ultrasound tomography.

My main interests at the moment are in inverse problems in optics (with Deeph Chana), including image deblurring, scanning confocal microscopy and compact discs, and in inverse problems in antenna theory (with Pelagia Neocleous). I am also working on several other inverse problems such as speech recognition and laser-diffraction particle sizing. All these problems are related by nasty underlying Fredholm integral equations of the first kind.

I am interested in the inverse problems related to the diffusion and transport equations, with applications to optical tomography. At the same time, I am also interested in the level-set techniques and their applications.

I work mostly in the analysis of dynamical multivariate signals in the biological/biomedical context. Most of the data that I study is neural imaging data, although I have been working quite a lot on imaging data of the heart taken using voltage-sensitive fluorescent dyes. I have used linear inverse methods that are local in the frequency domain for spectral and harmonic analysis of these signals with good results and can contribute knowledge about these methods. Because of the success I've had with these applications, I am interested in learning about other inverse problem approaches.

My past research dealt with question of uniqueness for the transport equation related to optical tomography and global reconstruction of two dimensional conductivity from boundary measurements. I need to learn more about the regularization methods used in numerical applications.

My scientific interest is in the field of inverse problems with a priori infomation about the exact solution (monotonicity, convexness, boundedness of the function or its derivatives). I want to find various applications for the solution of inverse problems for integral equations.

My research interests are the numerical methods for inverse problems, including the finite element methods, numerical analysis, fast efficient methods for optimization, and numerical methods for choosing regularization parameters.

Currently my research topic is transient elastography problem to recover shear wave property using interior time and space dependent displacement data. Mainly I am now doing theoretical works like uniqueness, nonuniquenes, stability. But discussions on algorithmic side are also welcomed. I am now very interested in anisotropic and incompressible model in elastic wave propagation.
My previous topic was incorporating EIT with MRI called MREIT. In the sense that MREIT is using also interior measurement, this problem has some similarities with my current elastography problem.