◾ Associate Professor in UMRAM
◾ Associate Professor in Department of Electrical and Electronics Engineering
Dr. Tolga Çukur is an Associate Professor in the Department of Electrical and Electronics Engineering, the National Magnetic Resonance Research Center (UMRAM), and the Neuroscience Graduate Program at Bilkent University. Dr. Çukur’s research is targeted at understanding the anatomy and function of biological systems in both normal and disease states. To this end, he develops cutting-edge imaging and computational methods for biomedical research. He designs ultra-fast magnetic resonance imaging (MRI) techniques for targeted diagnosis of vascular, musculoskeletal and neurological diseases. On the neuroscientific front, he uses functional MRI and modern statistical tools to study the function of human sensory and cognitive systems during complex natural behavior. More information about Dr. Çukur’s research program can be found on his lab’s website.
Dr. Çukur received his B.S. degree in Electrical and Electronics Engineering from Bilkent University in 2003. He continued his graduate studies in Electrical Engineering in the United States. There, he worked with Prof. Dwight G. Nishimura as a member of the Magnetic Resonance Systems Research Laboratory at Stanford University. During his doctoral work, he developed novel MRI methods to diagnose peripheral arterial disease, and to monitor treatment of cancer and other inflammatory diseases. He received his M.S. and Ph.D. degrees in 2005 and 2009, from the Department of Electrical Engineering, Stanford University, CA, USA.
He then moved to Berkeley, CA to pursue his postdoctoral research in systems neuroscience. He was a postdoctoral fellow in the Helen Wills Neuroscience Institute at the University of California, Berkeley during 2010-2013. He worked with Prof. Jack Gallant to build quantitative models of the human visual system under natural stimulation, and to infer the visual contents of the human brain. Since September 2013, he is a faculty member at Bilkent University.