Yuan Xue, PhD
Assistant Professor
Biomedical Informatics
Academic contact
Academic information
- Department: Biomedical Informatics
Research interests
- Computer Vision
- Medical Image Analysis
- Foundation Models
- Multimodal Learning
- Data-Efficient Learning
- Visual Perception and Reasoning
About
Biography
I am an assistant professor in the Department of Biomedical Informatics at The Ohio State University College of Medicine. My research focuses on computer vision, machine learning, biomedical informatics, and multimodal artificial intelligence (AI), with an emphasis on developing models that learn from limited, imperfect and heterogeneous data while improving their generalizability and reliability across different tasks and real-world settings.
My research group develops data-efficient learning methods, foundation models and multimodal AI approaches to analyze visual information and integrate it with other types of data. Our work spans medical image analysis, generative modeling and visual perception and reasoning, with a particular interest in how AI models capture visual structure, spatial relationships and contextual information. We also investigate ways to improve model adaptability, interpretability and generalization.
I collaborate with researchers and clinicians across disciplines to apply these methods to biomedical and clinical challenges, particularly in cardiovascular imaging, radiology and computational pathology. My goal is to advance medical AI methods that support more accurate disease characterization, diagnosis and risk prediction.
Credentials
Education
- Postdoctoral Training - Electrical and Computer Engineering
- Johns Hopkins University, Baltimore, MD, United States
- PhD - Informational Sciences and Technology
- Pennsylvania State University, University Park, PA, United States
- MS - Computer Science
- Lehigh University, Bethlehem, PA, United States
- BS - Electronic and information Engineering
- Huazhong University of Science and Technology, Wuhan, China
Research
Research interests
- Computer Vision
- Medical Image Analysis
- Foundation Models
- Multimodal Learning
- Data-Efficient Learning
- Visual Perception and Reasoning
- Structured Representation Learning
- Generative AI
- Trustworthy AI
- Cardiovascular Imaging
- Computational Pathology