About me

This is me

I am an applied mathematician and assistant professor for computational and mathematical methods for imaging at the University of Hamburg. Therefore, I am member of Center of Optimization and Approximation and associated with the Institute for Biomedical Imaging at the University hospital Hamburg Eppendorf (UKE).

My actual research covers large-scale inverse problems in biological and medical applications such as for example fluorescence microscopy, photo acoustic tomography and magnetic particle imaging. More precisely, I am working on variational regularization methods, dynamic inverse problems, Bayesian inversion, and approximation error modelling.

Members of the research group

  • Stephanie Blanke
  • Stasis Chuchurka
  • Dr. Tram Do
  • Dr. Milain Kas
  • Christiane Schmidt
Master students
  • Thorben Abel
  • Johannes Grün
  • Christopfer Fichtlscherer
  • Lena Zdun
Bachelor students
  • Amol Bains
  • Stephan Rickert

News


New members of our group

Welcome to Stephanie Blanke in our research group. She will work on the PhD project " Blood Flow modeling and estimation by magnetic particle imaging" within the research training group

New research training group

I am looking for a PhD candidate within the graduate school (project S3). The PhD topic will belong to the field of inverse problems, modelling and approximation with application to magnetic particle imaging. For more details, see the job call


New member of our group

Welcome to Tram Do in our research group. She will work on inverse problems in x-ray science.

New members of our group

Welcome to Milain Kas and Statis Chuchurka in our research group. They will both work on inverse problems in x-ray science.

Old news

My research

×

 

Published publications

Article

    Erb, W.; Weinmann, A.; Ahlborg, M.; Brandt, C.; Bringout, G.; Buzug, T.M.; Frikel, J.; Kaethner, C.; Knopp, T.; März, T.; Möddel, M.; Storath, M.; Weber, A.: Mathematical Analysis of the 1D Model and Reconstruction Schemes for Magnetic Particle Imaging. Inverse Problems, 34(5):2018.
doi:10.1088/1361-6420/aab8d1

    Bathke, C.; Kluth, T.; Brandt, C. & Maaß, P.: Improved image reconstruction in magnetic particle imaging using structural a priori information. International Journal On Magnetic Particle Imaging, 3(1):2017.
online availble here

    Storath, M.; Brandt, C.; Hofmann, M.; Knopp, T.; Salamon, J.; Weber, A. & Weinmann, A.: Edge preserving and noise reducing reconstruction for magnetic particle imaging. IEEE Transactions on Medical Imaging, 36(1):74-85, 2017.
doi:10.1109/TMI.2016.2593954

    Brandt, C., Maass, P., Piotrowska-Kurczewski, I., Schiffler, S., Riemer,O., and Brinksmeier, E.: Mathematical methods for optimizing high precision cutting operations. International Journal of Nanomanufacturing, 8(4):306–325, 2012.
doi:10.1504/IJNM.2012.048580.

    Brandt, C., Niebsch, J., Ramlau, R., and Maass, P.: Modeling the influence of unbalances for ultra-precision cutting processes. ZAMM - Journal of Applied Mathematics and Mechanics / Zeitschrift für Angewandte Mathematik und Mechanik, 91(10):795–808, 2011.
doi:10.1002/zamm.201000155.

    Piotrowska, I., Brandt, C., Karimi, H. R., and Maass, P.: Mathematical model of micro turning process The International Journal of Advanced Manufacturing Technology, Volume 45(1):33–40, 2009.
doi:10.1007/s00170-009-1932-z.

    Brandt,C., Niebsch, J., and Vehmeyer, J.: Modelling of ultra-precision turning process in consideration of unbalances. Advanced Materials Research, 223:839–848, 2011.
doi:10.4028/www.scientific.net/AMR.223.839

    Gossiaux, P.B., Aichelin, J., Brandt, C., Gousset, T., and Peigné, S.: Energy loss of a heavy quark produced in a finite-size quark-gluon plasma. Journal of Physics G: Nuclear and Particle Physics, 34(8):S817, 2007.
doi:10.1088/0954-3899/34/8/S103.

    Gossiaux, P.B., Peigné, S., Brandt, C., and Aichelin, J.: Energy loss of a heavy quark produced in a finite size medium. Journal of High Energy Physics, 4(04):012, 2007.
doi:10.1088/1126-6708/2007/04/012.

Thesis

    Brandt, C.: Regularization of Inverse Problems for Turning Processes. Ph.D. thesis, University of Bremen, Logos, 2012
available by Logos

Book chapter

    Andres, M., Blum, H., Brandt, C., Carstensen, C., Maass, P., Niebsch, J., Rademacher, R., Ramlau, R., Schröder, A., Stephan, E.-P., and Wiedemann, S.: Process Machine Interactions, Adaptive finite elements and mathematical optimization methods. Lectures Notes in Production Engineering. Springer, 2013.
doi:DOI:10.1007/978-3-642-32448-2.

    Brandt, C., Krause, A., Niebsch, J., Vehmeyer, J., Brinksmeier, E., Maass, P., and Riemer, O.: Process Machine Interactions, Surface Generation Process with Consideration ot the Balancing State in Diamond Machining. Lectures Notes in Production Engineering. Springer, 2013.
doi:DOI: 10.1007/978-3-642-32448-2.

    Piotrowska-Kurczewski, I., Brandt, C., Maass, P., and Riemer, O.: Micro Metal Forming, chapter Simulation technologies - Inverse Modelling, pages 368–379. Springer, 2013.

    Brandt, C., Piotrowska, I., Karimi, H., Niebsch, J., Ramlau, R., Krause, A., Riemer, O., and Maass, P.: Process machine interaction model for turning processes. International Journal of Control Theory and Applications, 1(2):145–153, 2008.

Conference proceedings (reviewed)

    Kluth, T.; Hahn, B.N. and Brandt, C.: Spatio-temporal concentration reconstruction using motion priors in magnetic particle imaging. Proceedings of the International Workshop on Magnetic Particle Imaging 2019, March 17-19. 2016, New York, USA, 2019.

    Brandt, C. and Hauptmann, A.: Fast temporal regularized reconstructions for magnetic particle imaging. Proceedings of the International Workshop on Magnetic Particle Imaging 2019, March 17-19. 2016, New York, USA, 2019.

    Storath, M., Brandt, C., Hofmann, M., Knopp, T. , Weber, A., Weinmann, A.: Fused lasso regularization for magnetic particle imaging. Proceedings of the International Workshop on Magnetic Particle Imaging 2016, March 16-18. 2016, Lübeck, Germany, 2016.

    Brandt, C., Niebsch, J., and Vehmeyer, J.: Modelling of ultra-precision turning process in consideration of unbalances. In Outeiro, J.C., editor, Proceedings of the 13th CIRP Conference on Modeling of Machining Operations, May 12-13. 2011, Sintra, Portugal, volume 223, pages 839–848. 2011. www.scientific.net/AMR.223.839>

    Niebsch, J., Ramlau, R., and Brandt, C.: On the interaction of unbalances and surface quality in ultra-precision cutting machinery. In SIRM 2011, Darmstadt, Germany. 2011.

    Brandt, C., Niebsch, J., Maass, P., and Ramlau, R.: Simulation of process machine interaction for ultra precision turning. In Proceedings of the 2nd International Conference on Process Machine Interactions, June 10-11, 2010, Vancouver, Canada. 2010.

    Brandt, C., Krause, A., Brinksmeier, E., and Maass, P.: Force modelling in diamond machining with regard to the surface generation process. In Proceedings of the 9th International Conference and Exhibition on Laser Metrology, machine tool, CMM and robotic performance, LAMDAMAP 2009, London, 30.06.-02.07.2009, pages 377–386. 2009.

    Gossiaux, P.B., Peigné, S., Brandt, C., and Aichelin, J.: Energy loss of a heavy quark produced in a finite-size quark-gluon plasma
doi:10.1088/0954-3899/34/8/S103. QM2006 Proceedings; 19th International Conference on Ultra-Relativistic Nucleus-Nucleus Collisions (QM2006), Shanghai, China, November 14-20, 2006.

Find my papers on researchgate

Upcoming talks

The next talks I will give ....

Spatio-temporal reconstruction for multi-patch magnetic particle imaging at the SIAM Imaging Conference, July 2020, Toronto

I will attend the "Inverse Problems: Modeling and Simulation" conference 2021 in Malta.

Conference talks

List of all talks in the last years

2019

Spatio-temporal regularization for 4D magnetic particle imaging
Synergistic Reconstruction Symposium, 3.-6. November 2019
Manchester, Great Britain
Invited by Dr. Jacob Jorgensen

Fast image reconstruction for 4D magnetic particle imaging
International congress on industrial and applied mathematics (ICIAM 2019), 15.-19.7.2019
Valencia, Spain
Invited by Kristian Bredies & Antonin Chambolle

Real-time reconstructions for 4D magnetic particle imaging
International conference on applied inverse problems (AIP 2019), 8.-12.7.2019
Grenoble, France
Invited by Felix Lucka, Tatiana Bubba, Sophia Coban & Samuli Siltanen

Fast temporal regularized reconstructions for magnetic particle imaging
International workshop on magnetic particle imaging 2019 17.-19.3.2019
New York, USA


Dynamic inverse problems in medical imaging
SIAM conference on computational science and engineering, 25.2-1.3.2019
Spokane, USA
Invited by Samuli Siltanen and Tatiana Bubba

Real time reconstructions for 4D magnetic particle imaging
Tomographic inverse problems: theory and application
Oberwolfach 2019, 27.1-2.2.2019



2018

Fast regularized reconstructions for dynamic tomographic applications
EUCCO 2018, 10.-12.6.2018
Trier, Germany
Plenary talk

Recovery from model errors in magnetic particle imaging - approximation error modeling approach.
Siam Imaging 2018, 5.-8.6.2018
Bologna, Italy
Invited by Traufiquar Khan and Cristiana Sebu

Challenges in image reconstruction for 4D magnetic particle imaging
GAMM, March 2018, 19.-23.3.2018
München, Germany
Invited by Felix Krahmer and Benedict Wirth


2017

Approximation error modelling for magnetic particle imaging
Conference on Applied Inverse Problems, May 2017
Hangzhou, China

2016

Edge Preserving Image Reconstruction for 4D Magnetic Particle Imaging
Imaging with modulated/incomplete data, 22.-24.9.2016
Graz, Austria


Image reconstruction for 4D Magnetic Particle Imaging
Inverse problems seminar at Helsinki University, 15.6.2016
Helsinki, Finland
Invited by Samuli Siltanen

Edge Preserving Image Reconstruction for 3D Magnetic Particle Imaging
SIAM Imaging 2016
23.-26.5.2016, Albuquerque, USA
Invited by Cecile Louchet

Fused Lasso Regularization for Magnetic Particle Imaging
International Workshop on Magnetic Particle Imaging IWMPI 2016
16.-18.3.2016, Lübeck, Germany

2015

Fused Lasso based Image Reconstruction for Magnetic Particle Imaging
Inverse Days 2015, 8.-10.12.2015
Lappeenranta, Finland

Sparse Image Reconstruction for Magnetic Particle Imaging
Mini-symposium on "Mathematical Methods for MPI" at the DMV 2015, 21.-25.9.2015,Hamburg
Invited by Wolfgang Erb

Photoacoustic Tomography: Sparse Image Reconstruction Using Shearlets
Applied Inverse Problems 2015
May 2015, Helsinki, Finland


2014

Photoacoustic Tomography: Sparse Image Reconstruction Using Shearlets
Seminar AG Imaging, University Münster,
3.12.2014
Invited by Martin Burger

Solving inverse problems for fluorescence microscopy
DSR seminar at the Helmholtz Institut München
7.7.2014
Invited by Frank Filbir

Sparse Image Reconstruction for Photoacoustic Tomography Using Shearlets
Workshop "Wavelets and Applications"
22.5.2014, Université Libre de Bruxelles, Belgium
Invited by Christine de Mol

Inversion of Photoacoustic Tomography using l1-norm Regularization of Shearlet Coefficients
SIAM Conference on Imaging Science
12-14.5.2014, Hongkong, China


Faltungsprobleme in der Biologie
Workshop Mathematics for Imaging
02.-04.04.2014, Bad Harzburg

Group photo of the participants
Image Reconstruction for Photoacoustic Tomography using Shearlets,
Mecklenburger Workshop "Approximationsmethoden und schnelle Algorithmen, 17-20.03.2014, Hasenwinkel



2013

Inversion of Photoacoustic Tomography using l1-norm Regularization of Shearlet Coefficients
Advances In Mathematical Image Processing, 30.09.-2.10.2013, Annweiler

Effective Discretization for Regularized Algebraic Reconstruction Techniques,
Applied Inverse Problems Conference AIP 2013, 1.-5.07.2013, Daejeon, Korea

2012

Sparsity Optimization in High Precision Cutting: an ODE based inverse problem
Inverse Problems: Modelling and Simulation 2012, 21.-26.05.2012, Antalya, Turkey

Parameter Identification in Ultra Precision Cutting: an ODE based Inverse Problem,
Oberseminar Analysis Universität Osnabrück, 14.05.2013, Osnabrück
(invited talk)

Parameteridentifikation bei gewöhnlichen Differentialgleichungen von hochpräzisen Zerspanprozessen,
Winterseminar der AG Technomathematik der Universität Bremen, 2012, 28.-29.2.2912, Ganderkesee

Magnetic particle imaging

MPI is a novel imaging modality for biomedical diagnostics ...

Magnetic Particle Imaging (MPI) is a novel imaging modality for biomedical diagnostics that determines the spatial distribution of magnetic nanoparticles by measuring the non-linear magnetization response of the particles to an applied magnetic field. The advantages of MPI are the high dynamic spatial and temporal resolution and that it does not employ any ionizing radiation.

Actual research projects on MPI

Flow estimation with a priori edge information for MPI/MRI data , joint work with Ikram Jumakulyyev and Tobias Kluth

Joint reconstruction in multi-color MPI, joint work with Martin Storath, Martin Hofmann and Tobias Knopp

Approximation error modelling for model-based MPI, joint work with Aku Seppänen

Time based regularization for 4D MPI, joint work Andreas Hauptmann

Mathematical methods for Magnetic Particle Imaging

In this scientific network founded by the German Research Foundation ....

Magnetic Particle Imaging (MPI) is a novel imaging modality for biomedical diagnostics that determines the spatial distribution of magnetic nanoparticles by measuring the non-linear magnetization response of the particles to an applied magnetic field. The advantages of MPI are the high dynamic spatial and temporal resolution and that it does not employ any ionizing radiation.

It is a joint research within of the scientific network "Mathematical methods for Magnetic Particle Imaging (MIEM). The network funded by the DFG consists of 9 researchers and it is lead by Dr. Wolfgang Erb from the University of Lübeck. For more information, see the official MIEM homepage.

Visit Network Webpage

Approximation error modeling in large scale inverse problems in imaging (09/2015-08/2018)



The main objective of this research is the development of mathematical methods for three imaging modalities in biological and medical applications: fluorescence microscopy (FM), photo-acoustic tomography (PAT) and magnetic particle imaging (MPI). All imaging applications have in common that the desired object such as in PAT and MPI the cancer cell in the human body is not directly observable but can be measured only indirectly.

In order to reconstruct the desired object, one has to solve the so-called inverse problem. In this project, mathematical methods for solving inverse problems are developed which consider modelling errors and uncertainties of the underlying models in the inversion. It is expected that the image reconstruction quality will be increased significantly in all three applications. In particular, the improvements are assumed to contribute to the development of PAT and MPI as medical imaging techniques in clinical practice.

This project is founded by the Academy of Finland.

Related Publications:

    Brandt, C.; Seppänen, A. : Recovery from errors due to domain truncation in magnetic particle imaging -- approximation error modeling approach. Journal of Mathematical Imaging and Vision, 2018.
10.1007/s10851-018-0807-z

Multi-messenger x-ray science - Solving inverse problems of x-ray crystallography with constraints by x-ray emission spectra (2019-2020)



Novel X-ray sources (in particular FELs) allow for the first time to study complex chemical reactions and catalysis in time-dependent manner. While x-ray diffraction gives access to the structure of the underlying system (atomic position), x-ray emission spectroscopy is a complementary technique, to gain chemical knowledge (such as, for example the spin and oxidation state of a particular reaction center). The time-dependent observation of the breaking and formation of electronic bonds is, however, still a delicate task and relies on the interpretation of experimental data based on models.

At the current stage, a few pioneering groups perform x-ray scattering and x-ray emission spectroscopy within one experimental set up and build models to interpret these data. The data analysis and the reconstruction of the underlying physical quantities (determination of the electron density by solving the phase problem of crystallography) are, however, performed independently and separately for each method. In this project, we aim for the next rigorous step, by developing a common data analysis, reconstruction and model building approach combining x-ray diffraction and emission spectroscopy. This novel holistic approach has the potential to strongly improve on the resolution of the chemically-relevant valence electronic density and their current densities.

This project is founded by the DESY Strategy Fund. It is a joint project with Prof. N. Rohringer and Prof. S. Techert from DESY.

Method and software development for solving the joint problem of x-ray diffraction and x-ray spectroscopy (2019-2021)



The proposed interdisciplinary project between the natural and mathematical/information sciences is understood as a kick-of project to develop novel x-ray data analysis methods for combined x-ray di raction and x-ray emission spectroscopy measurements at high-brilliance x-ray sources. While coherent x-ray di raction gives access to the structure (position of atoms) of a chemical compound or reaction unit, x-ray emission spectroscopy is a complementary and sensitive probe to the changes of the chemical bonds. The interpretation of the latter strongly relies on comparison with theoretically calculated spectra. Pioneering experiments at storage-ring based x-ray sources and x-ray free electron lasers (XFELs) have shown the possibility for combining x-ray di raction, x-ray scattering and x-ray emission spectroscopy in one high-quality experiment. Currently, the data analysis and reconstruction of the underlying physical quantities of interest (electron density, oxidation state, electron density, etc.) are undertaken independently from the two techniques. Here, we aim for a common data analysis and density reconstruction method, based on an underlying common electronic structre (quantum chemistry) model. Experimental x-ray diffraction and x-ray emission data will be directly implemented as constraints in the minimization approaches of ab-initio quantum chemistry methods, in the spirit of quantum crystallography. In this way chemical and structural information can be reconstructed in a coherent way.

This project is founded by the BMBF. It is a joint project with Prof. N. Rohringer from DESY/Department of physics(UHH).

Preprints

    Brandt, C.; Seppänen, A. : Recovery from errors due to domain truncation in magnetic particle imaging -- approximation error modeling approach. Journal of Mathematical Imaging and Vision, 2018.
10.1007/s10851-018-0807-z

    Brandt, C.; Hauptmann, A.: Real time reconstruction for 4D Magnetic Particle Imaging.

Research interests

I am currently working on inversion methods ...

I am currently working on inversion methods for magnetic particle imaging and as well as for inverse problems in X-ray science. Moreover, I am interested in dynamic inverse problems and regularization methods for these problems.

More generally my research interests are :
  • Medical and biological imaging
  • Modelling and simulation
  • Regularization with sparsity constraints
  • Dynamic inverse problems
  • Bayesian inversion and approximation error modelling
  • Coupled inverse problems in X-ray laser physics

Collaborations

Prof. Martin Storath

Hochschule Würzburg-Schweinfurt

Prof. Tobias Knopp, Dr. Martin Hofmann

Universitätsklinikum Hamburg-Eppendorf
Sektion für Biomedizinische Bildgebung

Institut für Biomedizinische Bildgebung
Technische Universität Hamburg

Dr. Wolfgang Erb

Università degli Studi di Padova
Italy

Prof.P. Maass, Dr. Tobias Kluth

Center for Industrial Mathematics
University of Bremen

Dr. Andreas Hauptmann

University College London
Great Britain

Dr. Aku Seppänen

University of Eastern Finland
Kuopio, Finland

Prof. Nina Rohringer

Deutsches Elektron-Synchroton
and Universiät Hamburg

Prof. Simone Techert

Deutsches Elektron-Synchroton
and Universiät Göttingen

Teaching

Actual courses

Inverse problems: numerical and statistical aspects

I will give a course on inverse problems together with Prof. Trabs during summer term 2020. The course will cover the classical theory of inverse problems as well as a statistical perspective.


Course webpage


Optimization

This course for Bahelor students will give an introduction to optimization. We will discuss standard algorithms for unconstrained and constrained minimization problems.


Course webpage

Supervision of theses

I am offering topics for thesis such that inverse problems, image reconstruction, optimization methods and Bayesian inversion related to applications in bio/medical imaging. There is also the possibility to have a joint project with the Medical university center Eppendorf (UKE). Current theses are:
  • L. Zdun, Stochastic first order methods for image reconstruction problems
  • T. Abel, Shearlet based reconstruction for dynamic X-ray data, Msc, University of Hamburg
  • S. Rickert, Methoden für nichtglatte Optimierungsprobleme, Bsc, University of Hamburg
  • C. Fichtlscherer, Regularized reconstructions of the single pixel Radon transform, Msc, University of Hamburg
  • J. Grün, Bayesian inversion and artifact reduction in magneti particle imaging, Msc, University of Hamburg
Examplary open topics can be fined here.

Previous Courses

Computational methods for imaging

Seminar on mathematical imaging University of Hamburg (winter 2019)

Convex optimization

Master course on Convex optimization The course covers classical theory of convex optimization and splitting methods for structured minimization problems. University of Hamburg (summer 2019)

Mathematik in der Medizin

Lothar Collatz Seminar (together with Stefan Heitmann), University of Hamburg (Summer 2019)

Inverse problems

Master course on inverse problems. We will treat the classical theory of linear inverse problems. University of Hamburg (Winter 2018/19)

Computer tomography

Master course on computer tomography. This is the first part of the inverse problems course. University of Hamburg (Winter 2018/19)

Optimierung

Bachelor course on optimization, University of Hamburg (Summer 2018)

Wirkung sucht Ursache - Inverse Probleme in den Naturwissenschaften

Lothar Collatz Seminar (together with Stefan Heitmann), University of Hamburg (Summer 2018)

Computer tomography

Course on computer tomography and short introduction to inverse problems, University of Hamburg (Winter 2017/18)

Optimization

Course on convex optimization in infinite dimesions, University of Hamburg (Summer 2017)

Inverse Problems

Exercises on inverse problems, University of Eastern Finland (Winter 2016/17)

Inverse Probleme

course together with Prof. Kunis, University of Osnabrück (Summer 2014)

Mathematics I for production engineering

2 tutorials, University of Bremen (winter 2012/13)

Analysis II

2 tutorials, University of Bremen ( summer 2012 )

Supervised theses and projects


  • L. Schönrock, Zeitbasierte Regularisierungsmethoden für medizinische Bilgebung, Bsc 2020, University of Hamburg
  • I. Glöckner, Reconstruction methods for multi-color magnetic particle imaging, Msc 2019, University of Hamburg, supervision together with Dr. M. Möddel, Prof. T. Knopp (UKE HH Eppendorf)
  • J. Muldoon, Visualisierung von Schallwellen mittels Lasterintrferomatrie und Radon-Transformation, Msc 2019, University of Hamburg, supervision together with Dr. Fischer (Institut für Musikwissenschaften, UHH)
  • D. Hailu, Reconstructions for dynamic x-ray data with help of shearlets, Msc, University of Hamburg
  • A. Geng, Improving calibration measurements in magnetic particle imaging by compressed sensing, Msc, University of Hamburg, superivision together with Dr. Martin Möddel (UKE HH Eppendorf)
  • I. Pabon, Adaptive spatio-temporal regularization for robust nonlinear registration in artifact-affected 4D medical images, Msc, University of Hamburg, supervision together with Dr. Rene Werner (UKE HH Eppendorf)
  • D. Hamann, Non-convex stochastic optimization, Bsc 2018, University of Hamburg
  • I. Jumakulyyev, Joint motion estimation and image reconstruction by incorporating a priori edge information, Msc 2018, University of Hamburg
  • L. Nawwas, Bias-reduction for sparsity promoting regularization in magnetic particle imaging, Msc 2018, University of Gdansk/University of Hamburg
  • T. Yu, Optimization for HDR brachytherapy,Msc 2017, University of Hamburg, supervision together with Prof. Schlaefer, TUHH
  • F. Lucchesi, Adversarial domain adaption for semantic segmentation Msc 2017, Unversity of Hamburg, supervision together with Prof. Vazquez, Universitat Autònoma de Barcelona
  • T. Heiskanen, Superresolution in microscopy, Bsc 2017, University of Eastern Finland
  • A. Pandey and I. Jumakulyyev, Optical flow estimation, Summer project 2017, University of Hamburg
  • T. Heiskanen, Deconvolution in fluorescence microscopy, Summer trainee 2016, University of Eastern Finland
  • P. Gralla, Mathematical methods for controlling ultra precise processes of machining, Bsc 2012, Supervision together with Dr. I. Piotrowska, University of Bremen.
  • P. Welz, Regenerative chattering for micro cutting processes, Bsc 2011, supervision together with Prof. P. Maass, University of Bremen.

Short CV

Academic positions

Since 03 2017

Assistant professor at the University of Hamburg.

Research group: Mathematical and computational methods in medical imaging

09/2015 - 02 2017

Academy post-doctoral researcher in the Inverse Problems group at the Eastern University of Finland in Kuopio.

  • Academy of Finland project "Approximation error modelling in large scale inverse problems in imaging" (2015-2018)

Kuopio

04/2013 - 08/2015

Post-doctoral researcher in the research group "Applied and Numerical Analysis" at the University Osnabrück working within the

  • Helmholtz young investigator group "Fast algorithms for biomedical imaging" (Helmholtz Zentrum München)

Osnabrueck

01/2008 - 04/2013

Research assistant in the at the WG Industrial Mathematics at the Center for Industrial Mathematics at the University Bremen, working within the

  • DFG priority program SPP1180, project "Mathematical methods for precision balancing of machine tool" (2008-2011)
  • SFB "Micro cold forming" (2012-2013)

Zetem

11/2007 - 12/2007

Research assistant in the research group "Solid physics" at the University Rostock, working within the SFB 652, project B1 Exciton matter in mesoscopic potentials

  • Tasks: Implementation of a phase retrieval algorithm for ultrashort laser pulses

Rostock

Education

2008 - 2012

Doctoral studies in the research group "Industrial mathematics" at the University Bremen

2012: Doctorate degree in mathematics, University Bremen

  • Thesis: "Regularization of Inverse Problems for Turning Processes"
  • Supervisor: Prof Peter Maass

Bremen

10/2001 - 08/2007

08/2007

Diploma studies in mathematics , University Rostock

Diploma degree in mathematics, University Rostock

  • Thesis: "Numerical phase reconstruction" (Numerical phase retrieval)
  • Supervisor: Prof Manfred Tasche

Rostock

10/2002 - 08/2007

10/2006 - 07/2006

08/2007

Diploma studies in physics, University Rostock

Master studies in physics, Erasmus exchange program, University Nantes

Master degree in physics, University Nantes (France)

  • Master thesis: "Energy loss of a parton in a quark-gluon-plasma"
  • Supervisor: Stéphane Peigné

Nantes

Contact me

Office adress

Universität Hamburg
Department of Mathematics
Bundesstraße 55
20146 Hamburg

Office: Geomatikum 116

Phone: +49 -40 42838 4076
Mail: Christina.Brandt(ad)uni-hamburg.de

Postal address

Universität Hamburg
Fachbereich Mathematik
Bundesstraße 55
20146 Hamburg
Germany