Dr. Shen received his Ph.D. in Computer Science from Dartmouth College in 2004. He is an Assistant Professor of Radiology and Imaging Sciences at the Indiana University School of Medicine (IUSM). He is a member of Center for Neuroimaging, Center for Computational Biology and Bioinformatics, Stark Neurosciences Research Institute, and Indiana Institute of Personalized Medicine at the IUSM. He is also affiliated with Department of Computer and Information Science and School of Informatics and Computing at IUPUI. His lab is focused on research and training in medical image computing and bioinformatics. He works with CS/informatics/statistics/engineering/neuroscience/genetics students and postdocs as well as other faculty collaborators on various neuroimaging and bioinformatics projects. In these projects, they study computational and informatics methods for analyzing structural, functional, molecular imaging data and relating them to genomic, clinical, cognitive and other biomarker data, with applications to various neuropsychiatric disorders. He is a co-leader of the Genetics Core of the Alzheimer’s Disease Neuroimaging Initiative (ADNI), an ongoing landmark imaging and biomarker study in AD: http://www.adni-info.org/. His research is primarily supported by NSF and NIH (NIA, NIBIB, NIAAA).
The Shen Laboratory develops and employs state-of-the-art computational and informatics methods and tools for independent and combined analyses of the following multi-modal, heterogeneous imaging, “omics”, and other biomarker data: (a) Imaging modalities: MRI (structural, fMRI, DTI, etc), PET; (2) “omics” data: GWAS (SNP, CNV), NGS, proteomics, pathways/networks; (c) other biomarker data: CSF and blood biomarkers, neuropsychological assessments, clinincal information. The disorders they are investigating include Alzheimer’s disease and mild cognitive impairment, breast cancer (neurocognitive effects of chemotherapy and hormonal interventions), schizophrenia, fetal alcohol syndrome and other conditions. Keywords describing their research areas include imaging genomics and bioinformatics, medical image computing, machine learning and data mining, shape modeling and surface morphometry, and imaging sciences and genetics in brain disorders.