Improving the Reproducibility of Computational Research

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Date(s) - 03/29/2017
11:00 am - 12:30 pm


As the data collection ability of nearly every area of science has ballooned, so has the potential for problematic research practices that can lead to irreproducible results.  In this National Science Foundation Directorate for Computer & Information Science & Engineering Distinguished Lecture, Russell Poldrack of Stanford University will discuss a set of approaches that we are developing to address this reproducibility crisis in the context of human neuroimaging research. These include an integrated platform for the analysis and open sharing of neuroimaging data, frameworks for the description of data and metadata, and the use of software containers and virtual machines to enhance computational reproducibility.  Poldrack will show how these approaches have the potential to enable a new era of reproducibility in science.

The lecture will be held at Room 110 of the NSF campus at 4201 Wilson Boulevard in Arlington, Virginia. It will also be webcast; to view the free webinar please register at:

Poldrack is the Albert Ray Lang Professor in the Department of Psychology at Stanford, and director of the Stanford Center for Reproducible Neuroscience.  His research uses neuroimaging to understand the brain systems underlying decision making and executive function.  His lab is also engaged in the development of neuroinformatics tools to help improve the reproducibility and transparency of neuroscience, including the and data sharing projects and the Cognitive Atlas ontology.

For more information, click here.

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