BEGIN:VCALENDAR VERSION:2.0 PRODID:IEEE vTools.Events//EN CALSCALE:GREGORIAN BEGIN:VTIMEZONE TZID:Turkey BEGIN:DAYLIGHT DTSTART:20380119T061407 TZOFFSETFROM:+0300 TZOFFSETTO:+0300 RRULE:FREQ=YEARLY;BYDAY=3TU;BYMONTH=1 TZNAME:+03 END:DAYLIGHT BEGIN:STANDARD DTSTART:20160907T000000 TZOFFSETFROM:+0300 TZOFFSETTO:+0300 RRULE:FREQ=YEARLY;BYDAY=1WE;BYMONTH=9 TZNAME:+03 END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTAMP:20200314T171700Z UID:1213D0BC-5E92-47E6-9507-CF4D9CF07F97 DTSTART;TZID=Turkey:20200313T133000 DTEND;TZID=Turkey:20200313T153000 DESCRIPTION:13 March 2020 (13:40): IEEE AP/MTT/EMC/ED Turkey Seminar Series (S.68)\n\nSpeaker: Assoc. Prof. Tolga Çukur\, Bilkent University\n\nTopi c: "Breaking Barriers in Structural and Functional Neuroimaging Through Ma chine Learning"\n\nLocation: Middle East Technical University\, Ankara\, T urkey\n\nAbstract: MRI offers an unrivaled opportunity to noninvasively ex amine the structure and function of the human brain in vivo. Yet\, MRI exa ms are hindered by limitations on spatiotemporal resolution and contrast o f acquired images as well as inefficient experimental designs. Classical a pproaches to reconstruction\, processing and analysis of imaging data ofte n fail to address these limitations. In this talk\, I will share an overvi ew of recent efforts in my lab to devise novel machine learning techniques in order to surpass fundamental barriers in structural and functional MRI . I will showcase examples where machine learning empowers rapid\, high-qu ality and high-sensitivity assessments in neuroimaging.\n\nBio: Dr. Çukur received his B.S. degree from Bilkent University in 2003\, and his Ph.D. degree from Stanford University in 2009\, both in Electrical Engineering. He was a postdoctoral fellow at Helen Wills Neuroscience Institute at Univ ersity of California\, Berkeley till 2013. Currently\, he is an Associate Professor in the Department of Electrical and Electronics Engineering\, UM RAM\, and Neuroscience Program at Bilkent University. His lab develops com putational imaging methods for understanding the anatomy and function of b iological systems in normal and disease states. He is the recipient of TUB ITAK Career Award (2015)\, TUBA-GEBIP Outstanding Young Scientist Award (2 015)\, BAGEP Young Scientist Award (2017)\, IEEE Turkey Research Encourage ment Award (2017)\, Science Heroes Association Young Scientist of the Year Award (2017)\, METU Prof. Dr. Mustafa Parlar Foundation Research Incentiv e Award (2019)\, and he is a senior member of IEEE (2017).\n\nSpeaker(s): Assoc. Prof. Tolga Cukur\, \n\nAnkara\, Ankara\, Türkiye LOCATION:Ankara\, Ankara\, Türkiye ORGANIZER:ozergul@metu.edu.tr SEQUENCE:0 SUMMARY:IEEE AP/MTT/EMC/ED TURKEY CHAPTER SEMINAR SERIES -- SEMINAR 68 URL;VALUE=URI:https://events.vtools.ieee.org/m/227127 X-ALT-DESC:Description: <br /><p><strong>13 March 2020 (13:40): &nbsp\;IEEE AP/MTT/EMC/ED Turkey Seminar Series (S.68)</strong></p>\n<p>Speaker: Asso c. Prof. Tolga &Ccedil\;ukur\, Bilkent University</p>\n<p>Topic: "Breaking Barriers in Structural and Functional Neuroimaging Through Machine Learni ng"</p>\n<p>Location:&nbsp\;Middle East Technical University\, Ankara\, Tu rkey</p>\n<p>Abstract: MRI offers an unrivaled opportunity to noninvasivel y examine the structure and function of the human brain in vivo. Yet\, MRI exams are hindered by limitations on spatiotemporal resolution and contra st of acquired images as well as inefficient experimental designs. Classic al approaches to reconstruction\, processing and analysis of imaging data often fail to address these limitations. In this talk\, I will share an ov erview of recent efforts in my lab to devise novel machine learning techni ques in order to surpass fundamental barriers in structural and functional MRI. I will showcase examples where machine learning empowers rapid\, hig h-quality and high-sensitivity assessments in neuroimaging.</p>\n<p>Bio: D r. &Ccedil\;ukur received his B.S. degree from Bilkent University in 2003\ , and his Ph.D. degree from Stanford University in 2009\, both in Electric al Engineering. He was a postdoctoral fellow at Helen Wills Neuroscience I nstitute at University of California\, Berkeley till 2013. Currently\, he is an Associate Professor in the Department of Electrical and Electronics Engineering\, UMRAM\, and Neuroscience Program at Bilkent University. His lab develops computational imaging methods for understanding the anatomy a nd function of biological systems in normal and disease states. He is the recipient of TUBITAK Career Award (2015)\, TUBA-GEBIP Outstanding Young Sc ientist Award (2015)\, BAGEP Young Scientist Award (2017)\, IEEE Turkey Re search Encouragement Award (2017)\, Science Heroes Association Young Scien tist of the Year Award (2017)\, METU Prof. Dr. Mustafa Parlar Foundation R esearch Incentive Award (2019)\, and he is a senior member of IEEE (2017). </p> END:VEVENT END:VCALENDAR