Affiliated Member - Foundations of Data Science
Victoria Stodden is an assistant professor of Statistics at Columbia University. She completed her PhD in statistics and her law degree at Stanford University. Her research centers on the multifaceted problem of enabling reproducibility in computational science. This includes studying adequacy and robustness in replicated results, designing and implementing validation systems, developing standards of openness for data and code sharing, and resolving legal and policy barriers to disseminating reproducible research.
She is the developer of the award winning "Reproducible Research Standard," a suite of open licensing recommendations for the dissemination of computational results. She is a co-founder of http://www.RunMyCode.org, an open platform for disseminating the code and data associated with published results, and enabling independent and public cloud-based verification of methods and findings. She is the creator and curator of SparseLab, a collaborative platform for reproducible computational research in underdetermined systems.
She was awarded the NSF EAGER grant "Policy Design for Reproducibility and Data Sharing in Computational Science." She serves on the National Academies of Science committee on "Responsible Science: Ensuring the Integrity of the Research Process" and the American Statistical Association's "Committee on Privacy and Confidentiality" (2013). She also serves as a member of the National Science Foundation's Advisory Committee on Cyberinfrastructure (ACCI), the Mathematics and Physical Sciences Directorate Subcommittee on "Support for the Statistical Sciences at NSF," and Columbia University's Senate Information Technologies Committee. She co-chaired a working group on Virtual Organizations for the NSF's Office of Cyberinfrastructure Task Force on Grand Challenge Communities in 2010. She is a nominated member of the Sigma Xi scientific research society, and serves on several advisory boards including hackNY.org, Galaxy, and the Science Exchange.