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      <image:title>Sook-Lei Liew - Sook-Lei Liew, PhD, OTR/L</image:title>
      <image:caption>Associate Professor, University of Southern California Sook-Lei Liew is an Associate Professor and Director of the Neural Plasticity and Neurorehabilitation Laboratory at the University of Southern California. She has joint appointments in the divisions of Occupational Science and Occupational Therapy, Biokinesiology and Physical Therapy, Biomedical Engineering, Neuroscience, and Neurology, and is a member of the USC Stevens Neuroimaging and Informatics Institute. She is the Chair of the ENIGMA Stroke Recovery Working Group, which uses big data neuroimaging and neuroinformatics approaches to understand brain-behavior patterns supporting recovery from stroke and which aggregates high-resolution MRI and behavioral data from thousands of patients collected across more than 50 research cohorts from 10 countries worldwide. She also is a co-director and co-founder of the USC SMART-VR (SensoriMotor Assessment and Rehabilitation Training) Center (smartvr.usc.edu). The overall goal of Dr. Liew’s research is to understand mechanisms of neural plasticity in healthy individuals and individuals after neurological injury that support a person’s ability to learn new skills and recover from brain injury. She has over 45 peer-reviewed publications, has given over 120 invited talks and conference presentations, and has received over $4.5 million in funding from agencies such as the NIH, National Science Foundation, US Army, and American Heart Association.</image:caption>
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      <image:title>David Kennedy - David Kennedy, PhD</image:title>
      <image:caption>Professor, University of Massachusetts Medical School Dr. Kennedy is a Professor of Psychiatry at the University of Massachusetts Medical School. He is Director of the Division of Neuroinformatics at the Child and Adolescent Neurodevelopment Initiative (CANDI). He has extensive expertise in the development of image analysis techniques and was a co-founder of the Center for Morphometric Analysis (CMA) at the Massachusetts General Hospital. His career has seen participation in the advent of such technologies as MRI-based morphometric analysis (1989), functional MRI (1991) and diffusion tensor pathway analysis (1998). He has long standing experience with development of neuroinformatics resources (Internet Brain Volumetric Database, Internet Brain Segmentation Repository, Internet Analysis Tools Registry), and participated as co-PI (PI: Bruce Rosen) of the morphometry Biomedical Informatics Research Network (mBIRN). Dr. Kennedy is the community liaison for the Neuroimaging Informatics Tools and Resources Clearinghouse (NITRC). In addition, he is a founding editor of the journal Neuroinformatics that debuted in 2003.</image:caption>
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      <image:title>James Finley - James Finley, PhD</image:title>
      <image:caption>Associate Professor, University of Southern California Dr. Finley directs the Locomotor Control Laboratory at the University of Southern California where he investigates how locomotion is controlled and adapted in the healthy and injured neuromuscular system. Dr. Finley’s lab develops theoretical models and experiments based on principles of neuroscience, biomechanics, and exercise physiology to identify the factors that guide learning and rehabilitation. Ultimately, the goal of his work is to design novel and effective interventions to improve locomotor control in individuals with nervous system damage.</image:caption>
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      <image:title>Keith Lohse - Keith Lohse, PhD, PSTAT</image:title>
      <image:caption>Associate Professor, Washington University in Saint Louis Dr. Lohse studies measurement, design, and analysis as they pertain to rehabilitation science and clinical practice. Dr. Lohse received a joint-PhD in Neuroscience, Cognitive Science, and Psychology from the University of Colorado in 2012, and is accredited as a Professional Statistician (PStat®) by the American Statistical Association. Dr. Lohse is passionate about making science as accessible as possible and, to that end, embraces open-access software (viz. R and Python) to help students learn data management, analysis, and visualization skills they can take everywhere and use anytime.</image:caption>
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