Special Virtual Seminar and Fireside Chat: Russ Poldrack, Stanford University
Note: This is a virtual seminar that will be broadcast in Olin Hall 305. Refreshments will be available outside Olin Hall 305 at 2:30 PM.
Title: Computational infrastructure to improve scientific reproducibility
Abstract: The massive increase in the dimensionality of scientific data and the proliferation of complex data analysis methods has raised increasing concerns about the reproducibility of scientific results in many domains of science. I will first present evidence that analytic flexibility in neuroimaging research is associated with surprising variability in scientific outcomes in the wild, even holding the raw data constant. These findings motivate the development of well-tested software tools for neuroimaging data processing and analysis. I will focus in particular on the role of software development tools such as containerization and continuous integration, which provide the potential to deliver automated and reproducible data analysis at scale. I will also discuss the challenging tradeoffs inherent in the usage of complex software by scientists, and the need for increased transparency and validation of scientific software.
Bio: Russell A. Poldrack is the Albert Ray Lang Professor in the Department of Psychology and Professor (by courtesy) of Computer Science at Stanford University, 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 Openneuro.org and Neurovault.org data sharing projects and the Cognitive Atlas ontology.