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Computational Research Day Keynotes

Guest Keynote

picture of Victoria StoddenVictoria Stodden, Associate Professor of Information Sciences, University of Illinois at Urbana

Reproducibility in Computational Research: Code, Data, Statistics, and Implementation—Louis Room 1:30 p.m. - 2:30 p.m.



Abstract:

Reproducibility in the computational sciences can be interpreted in increasingly expansive ways. The most narrow interpretation being re-execution (or even just preservation) of the computational steps that lead to the published scientific claims, using the same input data and parameter settings. The most expansive interpretation might be a completely independent implementation of an experiment designed to test the same scientific claim as a previously published work. In this talk I will start with the narrow interpretation and discuss steps by the community to enable reproducibility, and present a roadmap for achieving this goal. I will then propose steps to achieve the more expansive interpretation of reproducibility, including how we can compare and extend computational experiments to enhance scientific knowledge. I will present recent infrastructure research on experiment pipeline Abstractions for Improving Machine learning (AIM) to enable the comparison and extension of computational research.

About Victoria Stodden:

Victoria Stodden joined the School of Information Sciences as an associate professor in Fall 2014. She is a leading figure in the area of reproducibility in computational science, exploring how can we better ensure the reliability and usefulness of scientific results in the face of increasingly sophisticated computational approaches to research. Her work addresses a wide range of topics, including standards of openness for data and code sharing, legal and policy barriers to disseminating reproducible research, robustness in replicated findings, cyberinfrastructure to enable reproducibility, and scientific publishing practices. Stodden co-chairs the NSF Advisory Committee for CyberInfrastructure and is a member of the NSF Directorate for Computer and Information Science and Engineering (CISE) Advisory Committee. She also serves on the National Academies Committee on Responsible Science: Ensuring the Integrity of the Research Process.

Previously an assistant professor of statistics at Columbia University, Stodden taught courses in data science, reproducible research, and statistical theory and was affiliated with the Institute for Data Sciences and Engineering. She co-edited two books released 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. Stodden earned both her PhD in statistics and her law degree from Stanford University. She also holds a master’s degree in economics from the University of British Columbia and a bachelor’s degree in economics from the University of Ottawa. Read more.

The Northwestern Computational Research Day provides opportunities for University faculty, researchers, graduate students, and postdocs to discuss successful practices and challenges in research computing.

Keynote

headshot of Shane LarsonShane Larson, Associate Director of CIERA (Center for Interdisciplinary Exploration and Research in Astrophysics) and WCAS Research Associate Professor of Physics and Astronomy

At Home in a Storm of Stars: Observing, Simulating, and Pondering the Milky Way Galaxy—Louis Room 10:15 a.m. - 11:15 a.m.



Abstract:

The Milky Way galaxy is an elaborate storm of stars that is 10 billion years old and built of 400 billion stars. Historically our ideas about the nature and structure of the Cosmos have grown out of our attempts to understand the Milky Way. Four hundred years ago, we didn't even know what the Milky Way was, until the invention of the telescope revealed it was comprised of stars. Less than 100 years ago, we didn't know that if the Universe *was* the Milky Way, or if the Milky Way was simply a mote in a much vaster cosmic void. That question was resolved once again by telescopes and new theoretical ideas from Einstein's general relativity.

Today, we know a great deal more about the galaxy, but are still woefully limited by our inability to probe it. Large scale surveys, both with ground and space telescopes, are attempting to make unprecedented maps of the Milky Way. At the end of the 2020s, the gravitational wave observatory LISA will add to those maps a survey of the stellar graveyard of the Milky Way. Here at Northwestern we are engaged in a vast array of different computational and observational work to better understand the galaxy in which we live. In this talk we'll examine some of those projects, talk about what we hope to learn about the Milky Way, and speculate about what mysteries are still out of our reach.

About Shane Larson:

Shane Larson is a research associate professor of physics at Northwestern University, where he is the Associate Director of CIERA (Center for Interdisciplinary Exploration and Research in Astrophysics). He works in the field of gravitational wave astrophysics, specializing in studies of compact stars, binaries, and the galaxy.  He works in gravitational wave astronomy with both the ground-based LIGO project, and the future space-based detector LISA.

Shane grew up in eastern Oregon, and was an undergraduate at Oregon State University where he received his B.S. in Physics in 1991.  He received a Ph.D. in theoretical physics (1999) from Montana State University. He is an award winning teacher, and a Fellow of the American Physical Society.

He currently lives in the Chicago area with his wife, daughter and cats. He contributes regularly to a public science blog at writescience.wordpress.com, and tweets with the handle @sciencejedi. Read more.

 

Last Updated: 20 December 2018

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