Dr. Zhicong Yu Appointed as Assistant Professor at UC Santa Cruz
The Pattern Recognition Lab proudly congratulates Dr. Zhicong Yu on his appointment as Assistant Professor at the University of California, Santa Cruz, beginning January 2025.
Dr. Yu completed his Ph.D. at Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) at our lab in cooperation with Prof. Frederic Noo in Salt Lake City, USA, in 2013, following his M.S. at FAU (2009) and B.S. at Tongji University, China (2006). Over the past decade, he has significantly contributed to the advancement of X-ray imaging algorithms and system innovation, bridging the gap between academic research and real-world healthcare applications.
Before transitioning to academia, Dr. Yu spent over eight years in Research and Development within the healthcare industry. He was a Research Fellow at the CT Clinic Innovation Center at Mayo Clinic (2014-2016) and later worked extensively on premium CT scanners, photon-counting CT, helical cone-beam CT scanners, and advanced C-arm systems. His expertise spans CT image reconstruction, physics-based image corrections, artifacts mitigation, and imaging chain design, making him a leader in diagnostic and interventional radiology as well as radiation oncology.
Dr. Yu’s contributions are well-recognized in the field. He has published over 40 research articles and holds more than 20 U.S./PCT patents. His outstanding work has earned him the Rotblat Medal from Physics in Medicine and Biology (2021) and the President Award from Accuray (Team, 2022).
As he embarks on this new academic role, we look forward to seeing his continued impact in medical imaging and beyond. We extend our warmest congratulations and best wishes to Dr. Yu for this exciting new chapter at UC Santa Cruz.
About the Intelligent X-ray Imaging Lab
The Intelligent X-ray Imaging Lab is dedicated to pioneering research in advanced X-ray and CT imaging technologies, focusing on novel algorithms, system innovations, and clinical applications to enhance diagnostic and interventional radiology.
For more information, visit https://ixi.engineering.ucsc.edu/