Canberk Ekmekci

Hello, I am Canberk Ekmekci (pronounced Jahn-burk Ehk-mehk-jee), a Postdoctoral Appointee in the Imaging Group (XSD-IMG) at Argonne National Laboratory. I received my B.S. degree in Electrical and Electronics Engineering from Koç University, Istanbul, Turkey, in 2019. I received my Ph.D. in Electrical Engineering from the University of Rochester, Rochester, NY, in 2025, under the supervision of Prof. Mujdat Cetin.

My research interests lie primarily in the field of computational imaging, with a particular emphasis on developing and analyzing algorithms for imaging inverse problems. By leveraging techniques from machine learning, sampling, optimization, statistics, and uncertainty quantification, I aim to create trustworthy (robust, reliable, and interpretable) imaging frameworks that integrate data-driven and model-based methodologies in a principled manner. My current research explores topics such as:

• Bayesian Neural Network-Based Image Reconstruction Methods
• Calibration Techniques for Probabilistic Image Reconstruction Methods
• Automated Parameter Tuning for Iterative Image Reconstruction Algorithms
• Developing Tailored Algorithms for Specific (Imaging) Inverse Problems