Ender Konukoglu

Also known as Ender Konukoğlu

Ender Konukoglu is an associate professor at ETH Zurich who brings machine learning into biomedical image analysis. Raised in Istanbul, he studied electrical and electronics engineering at Bogazici University, completed a PhD at INRIA Sophia Antipolis, and joined ETH in 2016. He coauthored a decision-forest review and the BRATS brain-tumor benchmark paper, worked on image analysis and surgical support through SURGENT, and chaired MIDL 2022. A paper he coauthored won a best paper award at MICCAI in 2026; he now leads ETH's Biomedical Image Computing group and works on segmentation, uncertainty quantification and AI-driven medical image acquisition.

Now at: ETH Zurich
Born: 1981

Years link to their sources.

Timeline

2012

A review of decision forests

In 2012, he coauthors a review with Antonio Criminisi and Jamie Shotton in Foundations and Trends in Computer Graphics and Vision. The review presents random decision forests as a model for machine learning, computer vision and medical image analysis tasks.
2015

The BRATS tumor benchmark

In 2015, he coauthors the Multimodal Brain Tumor Image Segmentation Benchmark (BRATS) paper in IEEE Transactions on Medical Imaging. Organized with MICCAI 2012 and 2013, the benchmark applies twenty tumor segmentation algorithms to 65 multi-contrast MR scans of glioma patients.
August 2016

Assistant professor at ETH Zurich

Raised in Istanbul, he earns B.Sc. and M.Sc. degrees in electrical and electronics engineering at Bogazici University and completes a PhD at INRIA Sophia Antipolis under Nicholas Ayache. He works as a postdoctoral researcher at Microsoft Research Cambridge and at the Athinoula A. Martinos Center for Biomedical Imaging at Massachusetts General Hospital and Harvard Medical School before joining ETH Zurich in August 2016 as an assistant professor with tenure track in biomedical image computing.
2021

The SURGENT surgery project

In 2021, his group takes part in the SURGENT flagship project with Balgrist University Hospital. Its role is to interpret and analyse images and create models and simulations that help the surgeon throughout the operation.
July 2022

Co-chairing MIDL 2022

In July 2022, he serves with Bjoern Menze of Universität Zürich as a conference chair of the fifth International Conference on Medical Imaging with Deep Learning.
July–August 2022

Associate professor at ETH Zurich

In July 2022, the ETH Board names him an extraordinary professor in the Department of Information Technology and Electrical Engineering. In August 2022, he becomes an associate professor of biomedical image computing at ETH Zurich.
2026

A MICCAI workshop best paper

In 2026, he coauthors “Inter-Slice Acquisition Budget Allocation for Pathology Aware Accelerated MRI” with Meva Himmetoglu, and the paper receives a best paper award at the MLMI workshop at MICCAI 2026.
As of October 2026

Biomedical Image Computing group

As of October 2026, he is an associate professor in the Department of Information Technology and Electrical Engineering at ETH Zurich and leads the Biomedical Image Computing (BMIC) group. His research applies machine learning and computational methods to biomedical image analysis, including medical image segmentation, uncertainty quantification, anomaly detection, and AI-driven methods for improving medical imaging acquisition and analysis. In June 2026, he gives a keynote at the Symposium on Artificial Intelligence in Medical Imaging in Bern; in Fall 2026, he teaches ETH's Introduction to Estimation and Machine Learning.