About me

I am a Professor in the Department of Electrical and Electronics Engineering, and the Department of Neuroscience at Bilkent University, and the Director of the National Magnetic Resonance Research Center (UMRAM).

My research is targeted at developing computational imaging methods to examine the anatomy and function of biological systems in normal and disease states. To this end, my group develops cutting-edge imaging and data analysis methods for biomedical applications. We develop deep learning methods for magnetic resonance imaging (MRI) and computed tomography (CT), including physics-driven image reconstruction, multi-modal image synthesis, federated learning and vision-language models. On the neuroscientific front, we leverage functional MRI and machine learning to study the function of human sensory and cognitive systems during complex natural behavior. More information about my research program can be found on my lab's website.

Dr. Çukur is a faculty member at Bilkent University, Turkey since 2013, and currently serves as the Director of the National Magnetic Resonance Research Center (UMRAM). Prior to that, he was a postdoctoral fellow at University of California, Berkeley, CA. He worked with Prof. Jack L. Gallant in the Helen Wills Neuroscience Institute between 2010-2013. He devised novel machine learning techniques to build quantitative models of the human visual system under natural stimulation, and to infer the visual contents of the human brain.

He received his PhD in Electrical Engineering at Stanford University, CA. He worked with Prof. Dwight G. Nishimura and Prof. John M. Pauly as a member of the Magnetic Resonance Systems Research Laboratory between 2003-2009. During his doctoral work, he developed novel MRI acquisition and reconstruction methods to diagnose peripheral arterial disease, and to monitor treatment of cancer and other inflammatory diseases. Prior to his PhD, he received his B.S. degree in Electrical and Electronics Engineering from Bilkent University in 2003, as the class valedictorian.

Dr. Çukur was awarded Rambus Stanford Graduate Fellowship for his graduate studies. As a faculty member, he has received numerous prestigious awards including TUBITAK Career Award (2015), TUBA-GEBIP Outstanding Young Scientist Award (2015), BAGEP Young Scientist Award (2017), IEEE Turkey Research Encouragement Award (2017), Science Heroes Association Young Scientist of the Year Award (2017), METU Prof. Dr. Mustafa Parlar Foundation Research Incentive Award (2019), and TUSEB Aziz Sancar Incentive Award (2021). He is a Senior Member of IEEE (2017) and a Fellow of ISMRM (2024).

My lab develops computational imaging and machine learning methods for biomedical research, and uses them to study the anatomy and function of biological systems in health and disease.

In medical imaging, we develop physics-driven deep learning methods for MRI and CT reconstruction, generative models for multi-modal image synthesis, federated learning methods that let institutions train models together without sharing patient data, and vision-language models that link medical images with clinical text. We also work on magnetic particle imaging (MPI).

In neuroscience, we use functional MRI and machine learning to study how the human brain represents visual, auditory and linguistic information during natural behavior, and how attention reshapes these representations.

Each research area is described on the lab's research page, with selected papers. Code for most of our methods is available on GitHub.

(Full list of publications is here.)

• EEE 443 / EEE 543 Neural Networks.
• EEE 482 / EEE 582 Computational Neuroscience.
• GE 461 Introduction to Data Science.
• MATH 241 Engineering Mathematics I.
• EEE 351 Engineering Electromagnetics.
• EEE 202 Circuit Theory.