Prof. Dr. Dirk Lorenz

Leader of AG Inverse Problems and Imaging


(Photo Lukas Klose/Universität Bremen)

Office hours: During lecture time I hold weekly office hours (hybrid and in-person). You can find the dates on my profile page in Stud.IP - just navigate to my profile page, click on "Appointments", choose some date and show up either online (link in Stud.IP as well) or in my office.

CV

30.08.1978	born in Bremen.
1997 - 2002	study of Mathematics, Physics and Philosophy at the University of Bremen
08.2002	Diploma in Mathematics (minor subject Physics), title "Methoden der Multiskalenglättung"
2002 - 2004	researcher in the group "Technomathematik" at the ZeTeM
2004 - 2006	postdoc in the graduate program SCiE
02.2005	PhD in Mathematics, supervisor: Prof. Peter Maass, 2nd referee: Prof. Otmar Scherzer, title "Wavelet Shrinkage in Signal & Image Processing - An Investigation of Relations and Equivalences"
03.2006 - 08.2006	postdoc at the Electrical Engineering department at Technion, Haifa funded by the research training network HASSIP. Host: Prof. Y.Y. Zeevi
2006 - 03.2009	postdoc in the group "Technomathematik" at the ZeTeM
04.2009 - 09.2023	Professor at the Institute for Analysis and Algebra, TU Braunschweig
10.2023 - heute	Professor at the Center for Industrial Mathematics, Uni Bremen

Research Areas

• Inverse problems
• Signal and image processing
• Optimization
• Machine Learning

Projects

1. Sparsity and Compressed Sensing in Inverse Probleme (01.06.2008 - 31.05.2011)
2. BMBF-INVERS: Dekonvolution vs. Shrinkage: Mathematische Methoden für eine verbesserte Peakdetektion (01.10.2007 - 30.06.2010)
3. BMBF-INVERS: Regularisierung inverser Faltungsgleichungen in Besov-Skalen (01.10.2007 - 30.06.2010)
4. Parameteroptimierung für die High-Content-Analyse (01.12.2005 - 30.09.2007)
5. DFG-SPP 1114: Wavelet-shrinkage in der Bildverarbeitung – Eine Untersuchung von Zusammenhängen und Äquivalenzen (01.10.2002 - 30.09.2004)

Leader of Projects

1. Automated data-driven damage detection (01.10.2023 - 30.09.2026)
2. Training Data Driven Experts in Optimization (01.06.2020 - 01.12.2024)
3. Mathematics for Machine Learning for Graph-Based Data with Integrated Domain Knowledge (01.04.2020 - 31.12.2023)
4. Sparsity and Compressed Sensing in Inverse Probleme (01.06.2008 - 31.05.2011)

Courses (Selection)complete list

1. Mathematical Methods for Data Analysis and Image Processing (Wintersemester 2023/2024)
2. Convex Analysis (Wintersemester 2023/2024)
3. Seminar zur Regularisierung inverser Probleme (Wintersemester 2008/2009)

Theses (Selection)complete list

1. Die theoretische Analyse und Anwendung differentieller Methoden zur Flussberechnung (Kanglin Chen)
2. Image Inpainting (Inna Korabova)

Publications (Selection)complete list

1. D. Lorenz, J. Marquardt, E. Naldi.
   The degenerate variable metric proximal point algorithm and adaptive stepsizes for primal-dual Douglas-Rachford.
   Erscheint in Optimization

   online at: https://arxiv.org/abs/2302.13128

2. C. Brauer, N. Breustedt, T. de Wolff, D. Lorenz.
   Learning variational models with unrolling and bilevel optimization.
   Erscheint in Analysis and Applications

   online at: https://arxiv.org/abs/2209.12651

3. D. Lorenz, F. Schneppe, L. Tondji.
   Linearly convergent adjoint free solution of least squares problems by random descent.
   Inverse Problems, , 2023.

   DOI: 10.1088/1361-6420/ad08ed
   online at: https://arxiv.org/abs/2306.01946

4. L. Tondji, D. Lorenz, I. Necoara.
   An accelerated randomized Bregman-Kaczmarz method for strongly convex linearly constraint optimization.
   2023 European Control Conference (ECC).
   

   DOI: 10.23919/ECC57647.2023.10178390

5. L. Tondji, I. Necoara, D. Lorenz.
   Acceleration and restart for the randomized Bregman-Kaczmarz method.
   Zur Veröffentlichung eingereicht.

   online at: https://arxiv.org/abs/2310.17338

© Zentrum für Industriemathematik 2008-2023