Steven M Hodge MA
|Institution||University of Massachusetts Medical School|
|Address||University of Massachusetts Medical School|
365 Plantation Street, Biotech One
Worcester MA 01605
|Institution||UMMS - School of Medicine|
B.A. University of Wisconsin at Stevens Point (majors in Psychology and Music), Stevens Point WI, 1991.
M.A. Brandeis University (Cognitive Psychology, emphasis neuropsychology), Waltham MA, 1996.
Post-Graduate Research Experience
Research Associate at the Harold Goodglass Aphasia Research Center, Boston VA Medical Center, Boston MA, 1996-1999.
Research Associate in the 3D Imaging Service, Department of Radiology, Massachusetts General Hospital, Boston MA, 1999-2008.
Project Manager and Statistician at the Center for Morphometric Analysis, Department of Neurology, Massachusetts General Hospital, Boston MA, 2001-2008.
Other Experience and Memberships
Member of the American Statistical Association, 2009-present.
Participant at the Bipolar Statistical Summit: Methodologies to Advance Long Term Intervention Trials. National Library of Medicine, National Institutes of Health, Bethesda MD, Oct. 29, 2008.
Participant: Visiting Fellowship Program in Functional MRI. Center for Functional Neuroimaging, Massachusetts General Hospital, Boston MA, Oct. 21-24, 1998.
Mr. Hodge is the chief statistician at the Child and Adolescent Neurodevelopment Initiative (CANDI) in the Department of Psychiatry at UMASS Medical School. His primary interest is biostatistical data analysis of human brain imaging studies in order to further understand brain structure and function, especially in a broad spectrum of neurodevelopmental disorders (such as early onset bipolar disorder, schizophrenia, and autism). One initiative of this program is joint collaboration with the Neuroinformatics Program in the Department of Psychiatry, under the direction of Prof. David N. Kennedy. Together, they are developing an environment for the pooling of brain imaging data obtained from the research community. They are using this common pool of data to address massively multivariate statistical questions concerning, for example, the normative neuroanatomic development of the brain through childhood and the changes that are associated with mental illness.
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