Senior Lecturer/Associate Professor at Department of Information Technology, Vi3; Image Analysis
I am leading the Computer-assisted Applications in Medicine research (CAiM) group.
Here is a visual summary of my research interests.
For further information, please see my webpage at http://goksel.org/
A complete list of publications is available on my website above or on my Google scholar page,
For potential master's thesis projects, please contact by email.
Academic merits: Docent
Dr. Goksel received two BSc degrees in electrical engineering (2001) and in computer engineering/science (2002) from Middle East Technical University, Ankara, Turkey. He received his MASc (2004) and PhD (2009) degrees in the Department of Electrical and Computer Engineering at the University of British Columbia, Vancouver, Canada. Since 2014 he has been an assistant professor at the Department of Information Technology and Electrical Engineering at ETH Zurich, Switzerland. He founded and has been leading the Computer-assisted Applications in Medicine (CAiM) group within the institute Computer Vision Lab. In 2020, he joined the Department of Information Technology at Uppsala University, Sweden, as an associate professor, where he is affiliated with the Centre for Image Analysis as well as the Medtech Science and Innovation Centre.
Dr. Goksel has received the 2016 ETH Spark Award (for most promising invention of the year), the 2014 CTI Swiss MedTech Award, and the 2011 WAGS Innovation in Technology Award (for best dissertation in western North America). He supervised several master's and PhD students as well as postdoctoral fellows.
Computer-assisted Applications in Medicine (CAiM) Group, led by Orcun Göksel, is part of the newly-established Medtech Innovation and Science Centre as well as of the Centre for Image Analysis. CAiM is within the administrative Division of Visual Information and Interaction at the Department of Information Technology of Uppsala University in Sweden.
Basic and applied research in CAiM involve data analysis and information extraction, on topics lying at the intersection of multiple disciplines: computer science, engineering, and medicine. With the involvement of diverse and cross-disciplinary skill-set, the group aims to devise novel imaging and image analysis techniques, and develop them for clinical translation. The group’s efforts push the boundaries of diagnostic and surgical procedures as well as minimally-invasive interventions.
Research in CAiM is conducted in close collaboration with clinical as well as industrial partners, where the research results have a strong translational component, both clinically and commercially. To that end, CAiM aims to develop innovative diagnostic and interventional applications, focusing on data analysis from imaging to abstracting patient-specific models and representations, and from there to optimal intervention planning and intra-operative execution.
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