Hosted by the Department of Biostatistics
Attendees will learn how modern neuroimaging technologies, such as MRI, fMRI, EEG, diffusion tensor imaging, and PET, are being used to study the human brain in both normal development and neurological disorders. The event will highlight the statistical and methodological challenges involved in analyzing large, complex medical imaging data and will introduce advanced approaches developed to address these issues. Audience members should attend if they are interested in neuroscience, medical imaging, or data science, as the talk will connect cutting-edge statistical methods with real-world brain research applications. The presentation will cover several major research areas, including imaging tensor analysis, brain connectivity networks, multimodality analysis, and imaging causal analysis. The speaker will also present specific case studies to illustrate how these methods are applied in practice.
About the Speaker:
Lexin Li, Ph.D., is Professor and Division Chair, at the Department of Biostatistics and Epidemiology, Department of Statistics, and Helen Wills Neuroscience Institute, of the University of California, Berkeley. His research interests include neuroimaging analysis, deep brain stimulation, brain-computer-interface, reinforcement learning, ordinary differential equations, point process modeling, tensor data analysis, and network data analysis.
This event is open to the NYU Community (current students, faculty, and staff) only for in person attendance. The general public will only be allowed to participate virtually.