Associate Professor Victoria Stodden will give distinguished lectures at the University of Chicago on November 19 and Northwestern University on November 20. These lectures will focus on her reproducibility research as well as her work as a member of the U.S. National Academies of Sciences, Engineering, and Medicine (NASEM) Committee on Reproducibility and Replicability.
She will give the lecture, "Reproducibility is Not a Crisis. Now What? Next Steps for Advancing Computational and Data-enabled Science," as part of the University of Chicago's Center for Data and Computing Distinguished Speaker Series, and "The Lifecycle of Data Science: A Framework for Advancing Computational and Data-enabled Research," as part of Northwestern University's Computer Science Distinguished Lecture Series.
"In these talks, I will present the reproducibility definitions that emerged in our NASEM committee deliberations and discuss an abstract framework for conceptualizing and advancing data science as a discipline, called the Lifecycle of Data Science," Stodden said. "This framework integrates the disparate components of data-enabled discovery, from hardware provisioning to applications to dissemination standards for verification and re-use to ethics, and brings into contextual focus salient issues such as computational reproducibility, standards and policy, and curricular development."
Stodden is a leading figure in the area of reproducibility in computational science, exploring how we can better ensure the reliability and usefulness of scientific results in the face of increasingly sophisticated computational approaches to research. She is a member of the National Academy of Engineering Online Ethics Center Advisory Group, National Institute of Statistical Sciences (NISS), and member-at-large of the Statistics section of The American Association for the Advancement of Science (AAAS).
At Illinois, Stodden holds faculty affiliate appointments in the National Center for Supercomputing Applications (NCSA), Coordinated Science Lab, College of Law, Department of Statistics, and Department of Computer Science. She earned both her PhD in statistics from Stanford University and her law degree from Stanford Law School.