Members

Tician Schnitzler, MD is a postdoctoral research fellow at the University of California, San Francisco (UCSF) and an assistant physician in radiology at the Cantonal Hospital Aarau in Switzerland. Dr. Schnitzler’s work focuses on artificial intelligence in thoracic imaging, particularly on the development of clinical and imaging biomarkers for early lung cancer detection in interstitial lung disease (ILD), prediction of interstitial lung abnormality (ILA) progression to idiopathic pulmonary fibrosis (IPF), and clustering of IPF phenotypes to improve outcome prediction. He collaborates with numerous AI companies and startups and serves as a key interface between biomedical engineering and clinical implementation, while also currently pursuing a master’s degree in biomedical informatics and data science at the University of Mannheim to further enhance his skills in data-driven medical research. He leads several international multicenter AI collaborations and is the recipient of multiple competitive research grants, including the 2024 RSNA Research Fellow Grant, the Bangerter-Rhyner Foundation Grant 2023, and several research grants from the Swiss Society of Radiology.

Dr. Ali Nowroozi, MD graduated from Tehran University of Medical Sciences, Iran, in 2024, and has a long-standing background in programming and informatics. His current research focuses on advancing AI in radiology, including using AI to solve real world challenges as well as facilitating AI adoption into practice.

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Dr. Hong Yu, MD, PhD, is Associate Professor of Radiology, Vice Dean of the School of Medical Imaging, and Deputy Director of the Department of Radiology at the Affiliated Hospital of Zunyi Medical University in China. A cardiovascular radiologist with expertise in cardiac magnetic resonance imaging (CMR), his current research focuses on advanced CMR techniques and their clinical applications in ischemic heart disease.

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Dr. Kang Qi is a dedicated thoracic surgeon specializing in minimally invasive approaches to treat lung cancer, esophageal cancer, and mediastinal tumors. With advanced training in video-assisted thoracoscopic surgery (VATS) and robotic-assisted techniques, he performs complex oncologic resections with precision and efficiency. His clinical practice emphasizes a multidisciplinary approach to advanced-stage thoracic malignancies, integrating surgery with chemotherapy, radiation, and emerging systemic therapies to optimize patient outcomes. 

His research program is centered on two critical areas in thoracic oncology: 

1. Early Detection: Investigating novel imaging biomarkers to improve the diagnosis of early-stage thoracic tumors, enabling timely intervention. 

2. Postoperative Adjuvant Therapy: Exploring innovative treatment strategies, including targeted therapies and immune checkpoint inhibitors, to enhance survival and reduce recurrence in resected thoracic cancers. His work particularly focuses on identifying predictive biomarkers for treatment response and developing personalized adjuvant regimens. 

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Brandon Schonour is a 4th year medical student at the University of South Alabama in Mobile, Alabama, with a research interest in image quality optimization. His current research work focuses on identifying predictors of image degradation in respiratory-triggered pulmonary MRI at 0.55T, with the goal of improving diagnostic reliability in low-field imaging. Through this research, he aims to advance the clinical utility of low-field MRI overall.

Jaewon Jung is a 4th year medical student at Yonsei University in Korea, with a strong academic interest in the intersection of medical imaging and artificial intelligence. Her research focuses on developing novel AI-assisted imaging biomarkers to enhance diagnostic accuracy and support individualized patient care. Through active collaborations with researchers at UCSF and Yonsei, she seeks to build clinically meaningful AI tools that improve workflow efficiency and ultimately advance patient outcomes.

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