معرفی
Dr. Junhao Wen is an Assistant Professor of Computational Neuroscience at the Department of Radiology, Columbia University Irving Medical Center. He is also an Affiliated Member of the Health Analytics Center. His interdisciplinary work bridges advanced artificial intelligence and biomedical data to investigate human aging and disease mechanisms.
Dr. Wen's research focuses on integrating AI and machine learning with multi-organ imaging (e.g., brain MRI) and multi-omics data (including genetics and proteomics). His work aims to uncover biomarkers and mechanistic insights into neurodegenerative diseases and aging processes. This positions him at the forefront of computational biomedicine and precision health analytics.
His scientific approach combines deep learning, statistical modeling, and large-scale biomedical datasets to develop predictive models of disease progression. These methods are applied across diverse populations to enhance early diagnosis and intervention strategies.
The Health Analytics Affiliation underscores his role in advancing data-driven healthcare solutions at Columbia. While no specific publications or awards are listed in the source text, his research trajectory reflects strong engagement with cutting-edge computational methodologies in medicine.
Dr. Wen has previously held positions as a postdoctoral researcher at the University of Pennsylvania and as an Assistant Professor at the University of Southern California. He earned his Ph.D. from Sorbonne University in 2019, establishing a foundation in computational methods applied to neuroscience and biomedical data.
He advises graduate students and may lead a research laboratory focused on AI-driven health discovery, though specific advisees are not named. His work likely involves collaboration across departments and institutions, supported by grants in AI, neuroscience, and aging research, although specific funding sources are not mentioned.
Dr. Wen's laboratory, accessible via https://labs-laboratory.com/, serves as a hub for interdisciplinary research in computational neuroscience and health analytics.
