A Short Biography

VICTORIA STODDEN is Associate Professor in the Department of Industrial and Systems Engineering at the University of Southern California.

She received a Ph.D. in Statistics from Stanford University and a Law Degree from Stanford Law School. She graduated magna cum laude with her Bachelor’s in Economics from the University of Ottawa and holds a master’s degree in Economics from the University of British Columbia. She held the Kauffman Innovation fellowship at Yale Law School and was a Berkman Klein fellow at Harvard Law School. She was a postdoctoral researcher at MIT and has held faculty positions at the University of California Berkeley, Columbia University, and a tenured position at the University of Illinois at Urbana Champaign.

Stodden is an internationally recognized leader in improving the reliability of scientific results in the face of increasingly sophisticated computational approaches to research: understanding when and how inferences from data are valid and reproducible, what it means to have replicated a result, the effect of big data and computation on scientific inference, the design and implementation of scientific validation systems, standards of openness and transparency for data and code sharing, and resolving legal and policy barriers to disseminating reproducible research.

She has published more than 50 papers in scientific journals and conference proceedings, and has co-edited two professional books, published in 2014, Privacy, Big Data, and the Public Good: Frameworks for Engagement, published by Cambridge University Press and Implementing Reproducible Research, published by Taylor & Francis.

In 2009 she won the Access to Knowledge Kaltura prize for her publication on legal issues in reproducible research and scientific innovation. She has served on the National Academies of Science, Engineering, and Medicine committees: “Reproducibility and Replication in Science” and “Fostering Research Integrity.” She co-chaired the National Science Foundation Advisory Committee for Cyberinfrastructure and was a member of the National Science Foundation Directorate for Computer and Information Science and Engineering (CISE) Advisory Committee. She has been quoted in The Economist (2013) and interviewed by publications such as Nature (2016) on reproducibility in science.

She also testified on scientific reproducibility before the Congressional House Committee on Science, Space and Technology for the March 5, 2013 hearing on Scientific Integrity & Transparency.

She is PI on NSF awards #1941443 EAGER: Reproducibility and Cyberinfrastructure for Computational and Data-Enabled Science, and #1839010: EAGER: Preserve/Destroy Decisions for Simulation Data in Computational Physics and Beyond; and she is co-PI on the NSF grant #1541450: CC*DNI DIBBS: Merging Science and Cyberinfrastructure Pathways: The Whole Tale.

Her ORCID ID is 0000-0003-2015-7825.


A 705x990 jpg image is available here, and a 1749x1662 jpg here.

External Appointments
I'm an Affiliate Scholar with the Center for Internet and Society at Stanford Law School, a Faculty Affiliate of the Meta-Research Innovation Center at Stanford (METRICS).


My research takes a systems approach to understanding how and when inferences from data are valid and reproducible. My group focuses on understanding the effect of big data and computation on scientific inference, for example 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.

I created the "Reproducible Research Standard," a suite of open licensing recommendations for the dissemination of computational results, and winner of the Kaltura Prize for Access to Knowledge.

I am co-PI on NSF award:

I have served as PI on several NSF awards:

and I was PI on the Sloan Foundation grant Facilitating Transparency in Scientific Publishing.

Software Projects

I founded the open source project ResearchCompendia.org, designed to study the verification of code and data associated with published results, enable independent and public cloud-based validation of methods and findings. I am a co-founder of RunMyCode.org, a platform connecting data and code to published articles.

As part of my PhD dissertation, I created SparseLab, a collaborative platform for reproducible computational research in underdetermined systems.

Service, Boards, and Conflicts of Interest

The service aspects of my job are among those I enjoy the most. I endeavor to minimize any potential influence this service could have on other areas where I am active, however I'm disclosing my relationships to let people know of any possible influences.

Editorial Service
My Institution

My employer is the University of Southern California.

Previous Service

Fun Facts

My Erdös Number is 3.

I was a varsity crew member for the first two years of my undergraduate degree, then competed at the Club level for the next two years with the Ottawa Rowing Club. I'd race in any boat but my speciality was the lightweight eight, port or starboard.