School of Humanities and Sciences
Showing 11-15 of 15 Results
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Oscar Daniel Mier
Masters Student in Symbolic Systems, admitted Autumn 2022
BioOscar Daniel Mier, a driven neuroscience professional and Master of Science candidate in Symbolic Systems at Stanford University, exemplifies unwavering dedication to neuroscience, neuroimaging, and the welfare of veterans. With a Bachelor of Science in Neuroscience from the University of California, Riverside, and graduate training in Neuroimaging and Informatics from the University of Southern California, Oscar's academic journey has propelled him through a multifaceted career. His experience includes working as a Clinical Research Coordinator at the Etkin Lab, the United States Marine Corps, and a Site Lead Clinical Research Coordinator at the U.S. Department of Veteran Affairs Palo Alto Healthcare System.
Oscar's passion for helping others shines through his work as a Mobile Training Team S.T.E.M. Fellow with the Warrior-Scholar Project, where he tutored and mentored student veterans and active service members and coordinated academic boot camps at prestigious universities. In his most recent position as a Technical Solutions Engineer at Alto Neuroscience, Oscar managed neuroimaging data and trained clinicians on clinical study paradigms. As he continues his academic journey at Stanford, Oscar brings his extensive experience, expertise, and unwavering commitment to the forefront, poised to make a lasting impact in the field of neuroscience and the lives of veterans. -
Mark Musen
Stanford Medicine Professor of Biomedical Informatics Research, Professor of Medicine (Biomedical Informatics) and of Biomedical Data Science
Current Research and Scholarly InterestsModern science requires that experimental data—and descriptions of the methods used to generate and analyze the data—are available online. Our laboratory studies methods for creating comprehensive, machine-actionable descriptions both of data and of experiments that can be processed by other scientists and by computers. We are also working to "clean up" legacy data and metadata to improve adherence to standards and to facilitate open science broadly.
