I am working as a postdoctoral researcher with Prof. Ender Konukoglu in Biomedical Image Computing (BMIC) group in the Computer Vision Lab. (CVL), ETH Zurich, Switzerland.

My research is focused around the general theme of developing Machine Learning algorithms with applications to Biomedical Image Analysis and Computer Vision. Lately, I am particularly interested in learning from limited annotations and making Machine Learning models trustworthy to be able to use them clinical settings. See research page for more details.

Short Bio

I joined ETH Zurich in June 2019. Prior to this, I was working as a Senior Research Engineer in ARM Ltd. where I was developing hardware-efficient image processing methods for improving image quality in mobile displays. In 2017, I obtained my Ph.D. degree from Computer Science and Engineering department, Sabanci University, Turkey under the supervision of Prof. Mujdat Cetin. During my Ph.D., I worked on developing Bayesian methods for object segmentation by exploiting nonparametric shape priors.

News

• Our new preprint titled “Constrained Optimization to Train Neural Networks on Critical and Under-Represented Classes” is out. [Arxiv] [Code]
• Our new preprint titled “Task-agnostic out-of-distribution detection using kernel density estimation” is out. [Arxiv] [Code]
• Our paper titled “Contrastive learning of global and local features for medical image segmentation with limited annotations” is accepted as oral presentation in Neurips 2020. [Paper] [Code]
• I am selected among the top 10% high-scoring reviewers in Neurips 2020.
• I am selected among the outstanding reviewers in MICCAI 2020.
• Our paper titled “Test-Time Adaptable Neural Networks for Robust Medical Image Segmentation” is accepted in MEDIA, Elsevier. [Paper] [Code]
• Our paper titled “Semi-supervised Task-driven Data Augmentation for Medical Image Segmentation” is accepted in MEDIA, Elsevier. [Paper] [Code]