Mathematics in Imaging

24 June 2019 – 27 June 2019 Messe München, Munich, Germany

This meeting is an opportunity to gather people from optics, mathematics, and signal processing to cross-fertilize these fields with discussions on novel technologies, methodologies and challenges.
Communications that are not directly related to imaging, but could be of interest to the field or unsolved challenges in optics, requiring advanced signal processing tools are particularly welcome.


1. Foundations in electromagnetics and imaging

  • Propagation of waves
  • Scattering (e.g. surface scattering, volumetric scattering)
  • Phase, statistical optics, coherence optics
  • Image formation (e.g. tomography, telescope, microscopy, remote sensing, 
    multi-aperture system)
  • Theory and algorithms of optical element designs (e.g. computer generated hologram,
    volume holograms, photonic elements)
  • Nonlinear optics
  • Linear and nonlinear spectroscopy

 ​​2. Foundations in mathematics and signal processing

  • Variational or Bayesian regularization of inverse problems (e.g. total variation or frame
    based regularization)
  • Bilinear inverse problems (e.g. blind deblurring, self-calibration)
  • Sampling theory (e.g. compressive imaging, adaptive sampling)
  • Theory and algorithms of learning techniques (e.g. dictionary learning, neural networks)
  • Optimization theory and algorithms for convex and nonconvex problems (e.g. phase
    retrieval, inversion of multiple scattering)



  • Amit Ashok, University of ArizonaUnited States 
    Role of Coherence in Fundamental Limits of Imaging: Two Case Studies
  • Sohail Bahmani, Georgia Tech Research InstituteUnited States 
    Estimation from nonlinear observations via convex programming
  • Daniel Brunner, CNRSFrance 
    Limits and Applications of Diffractive Coupling
  • Oliver Cossairt, Northwestern UniversityUnited States
  • Carlos Fernandez-Granda, New York UniversityUnited States 
    A Sampling Theorem for Deconvolution
  • Mohammad Golbabaee, University of BathUnited Kingdom 
    Robust Algorithmic Weakening for Solving Big Data-driven Inverse Problems in Medical Imaging
  • Tapio Helin, Lappeenrannan Teknillinen YliopistoFinland 
    Correlation-based Imaging in Adaptive Optics
  • Felix Krahmer, Technische Universität MunchenGermany 
    Mathematical methods for ptychography with limited information
  • Andreas Menzel, Paul Scherrer InstitutSwitzerland 
    Reconstruction differences between x-ray ptychography and x-ray Fourier ptychography
  • Ozan Oktem, Kungliga Tekniska HogskolanDenmark 
    Bayesian inversion for inverse problems in imaging through machine learning
  • Rafael Piestun, University of Colorado at BoulderUnited States 
    Fast wavefront control for imaging in complex media
  • Nelly Pustelnik, Ecole Normale Supérieure de LyonFrance 
    Combining scale-free descriptors and nonsmooth optimization for texture segmentation. Application to multiphasic flow
  • Karin Schnass, University of InnsbruckAustria 
    Size-Adaptive Dictionary Learning
  • Fiorella Sgallari, Alma Mater Studiorum - Univ di BolognaItaly 
    Flexible space-variant directional regularization for image restoration problems
  • Markus Testorf, Dartmouth CollegeUnited States 
    Superresolution Imaging and Superoscillation Design



  • Lei Tian, Boston University, United States , General Chair
  • Ulugbek Kamilov, Washington University in St. Louis, United States , Program Chair
  • Pierre Weiss, Université de Toulouse, CNRS, France , Program Chair
  • Laure Blanc-Féraud, CNRS, France
  • Katie Bouman, California Institute of Technology, United States
  • Kristian Bredies, Karl-Franzens-Universitat Graz, Austria
  • Raymond Chan, Chinese University of Hong Kong
  • Yuejie Chi, Carnegie Mellon University
  • Denis Fortun, CNRS, France
  • Josselin Garnier, Ecole Polytechnique, France
  • Sylvain Gigan, Sorbonne Université , France
  • Ryoichi Horisaki, Osaka University, Japan
  • Roarke Horstmeyer, Duke University, United States
  • Clem Karl, Boston University, United States
  • Shalin Mehta, Chan Zuckerberg Biohub, United States
  • Konrad Schöbel, Carl Zeiss AG, Germany
  • Yoav Shechtman, Technion, Israel Institute of Technology, Israel
  • Tanja Tarvainen, University of Eastern Finland, Finland
  • Laura Waller, University of California Berkeley, United States
  • Renjie Zhou, Chinese University of Hong Kong, Hong Kong


Plenary Session

Domenico Bonaccini Calia

European Southern Observatory, Germany

The Ongoing Adaptive Optics Revolution

Adaptive Optics enhances the performance of imaging systems down to the diffraction limit and more in general can flatten the wavefronts in optical systems in real time. It is a technology now increasingly used in astrophysics, ophthalmology, microscopy, beam shaping of high power lasers for industry, beam pre-shaping for large baseline interferometry, precision microelectronics fabrication, satellite free space optical communications, quantum computing, to name a few.    Adaptive Optics technologies are very lively transforming and on the move.

We will review together the status of Adaptive Optics Technologies. Some of the most beautiful technological and application achievements will be shown, including recent developments obtained observing our Universe, with novel Laser Guide Star Adaptive Optics installations at the largest, more remote astrophysical observatories in the world.

About the Speaker

Domenico Bonaccini Calia has been working as a physicist at the European Southern Observatory ( for over 24 years, where he currently has an international member staff position.

He obtained his Masters in physics at the University of Florence, Italy, then completed a PhD in astrophysics, and a postdoc period at the Sac Peak National Solar Observatory in New Mexico, USA. On his return to Italy, Domenico held for 8 years a staff position at the Arcetri Astrophysical Observatory, in Florence, where he formed the adaptive optics group in 1990, before moving to ESO, Germany, in 1995.

At ESO he worked in the adaptive optics group and in 2000 he has formed the Laser Guide Star Systems Department, serving as Head of Department until 2010. He has contributed to two laser guide star facilities now installed on the ESO Very Large Telescopes in Chile, is supporting the ESO ELT activities for the new design of its six laser guide star units, and is currently responsible for the laser guide star systems research and development activities at ESO, under the Technology Development program.

D. Bonaccini Calia received the innovation award from the german Leibinger Stiftung in 2016, became a Fellow of The Optical Society in 2018 for its contribution to the progress of photonics in astronomical instrumentation, shared the 2018 Paul F. Forman Team Engineering Excellence Award and as been inventor  in 4 different patents related to wavefront correctors and novel laser systems.

Dongheui Lee

Technical University of Munich (TUM), Germany

Robot learning from Human Guidance

As a fundamental cornerstone in the development of intelligent robotic assistants, the research community on robot learning has addressed autonomous motor skill learning and control in complex task scenarios. Imitation learning provides an efficient way to learn new skills through human guidance, which can reduce time and cost to program the robot. Robot learning architectures can provide a comprehensive framework for learning, recognition and reproduction of whole body motions.

About the Speaker

Dongheui Lee is Associate Professor of Human-centered Assistive Robotics at the TUM Department of Electrical and Computer Engineering. She is also director of a Human-centered assistive robotics group at the German Aerospace Center (DLR). Her research interests include human motion understanding, human robot interaction, machine learning in robotics, and assistive robotics.

Previously, she was an Assistant Professor at TUM (2009-2017), Project Assistant Professor at the University of Tokyo (2007-2009), and a research scientist at the Korea Institute of Science and Technology (KIST) (2001-2004). She obtained a PhD degree from the department of Mechano-Informatics, University of Tokyo, Japan in 2007. She was awarded a Carl von Linde Fellowship at the TUM Institute for Advanced Study (2011) and a Helmholtz professorship prize (2015).