“Data-driven approaches for uncovering brain mechanisms”

Hosted by the Mallinckrodt Institute of Radiology (MIR)

Short Bio: Ganesh Chand, PhD is a biophysicist trained in multi-modal neuroimaging, quantitative modeling and machine learning (ML)/artificial intelligence (AI) methods. He has developed neural signal analysis and brain image analysis methodologies, proposed novel ML/ AI models, and applied these as well as other advanced quantitative modeling techniques to understand the underlying brain mechanisms in health and diseases such as mild cognitive impairment/preclinical Alzheimer’s disease, schizophrenia, psychosis spectrum symptoms etc. He is currently an Instructor in Radiology at WUSTL. He completed his postdoctoral training in neuroimaging and ML at the University of Pennsylvania (Department of Radiology) before joining WUSTL. Before that, he also received two years postdoctoral training in neuroimaging at Emory University School of Medicine. He has obtained a BS in physics and MS in computational physics from Tribhuvan University (Nepal). He has completed a PhD in biophysics (specialization in neurophysics/neuroimaging) from Georgia State University. In this talk, he will discuss the various neural signal analysis and brain image analysis methodologies and their potential applications to uncover the underlying brain mechanisms in health and diseases, especially mild cognitive impairment/preclinical Alzheimer’s disease, schizophrenia, psychosis spectrum symptoms.

For inquiries contact Margaret Morton.