Zafer Dogan

Short biography

Zafer Dogan got his Ph.D. degree in Electrical Engineering from Ecole Polytechique Federale de Lausanne (EPFL), Switzerland, in April 2015. His research areas include signal and image processing (in particular, sparse signal representations, sampling and approximation, multi-resolution analysis and finite rate of innovation representations in functional neuroimaging) and inverse problems in nonlinear tomography (in particular, meshfree methods in inverse source and scattering problems for nonlinear ultrasound- and photoacoustic-tomography). Before his Ph.D., he got his B.Sc. degree from Middle East Technical University (METU) and M.Sc. degree from EPFL both in Electrical and Electronics Engineering in 2009 and in 2011, respectively. Dr. Dogan continues his career as a postdoctoral researcher in Campus Biotech at MIPLAB jointly affiliated to EPFL and University of Geneva.

Main activities

• Developing algorithms for sparse signals models
  • Processing and analyzing large datasets to detect underlying signals and patterns
  • Using a data-driven approach to design and develop innovative models
• Building tools in MATLAB and C++ for solving inverse problems in image and signal processing.
  • Detection of sparse objects in tomography and radar applications
  • Developing prediction frameworks in neuroimaging.
• Teaching the theory and practice of image processing with integrated lab sessions in JAVA
• Supervising student projects on mathematical signal processing