Upcoming Events

Webinars

• • Computational Reproducibility: Challenges, Solutions, and Cultivating Trust in Data-Driven Science, March 13th, 12pm CST with Juliana Freire, Professor of Computer Science and Data Science at NYU and co-director of the Visualization Imaging and Data Analysis Center (VIDA) at the Tandon School of Engineering.

The abundance of data, accessible computing power, and storage has revolutionized science and ushered an era of data-driven scientific discoveries. However, this paradigm shift has raised critical questions about how to adapt the scientific process to ensure transparency and reproducibility in the era of data and computation. In this talk, Juliana Freire (Professor of Computer Science and Data Science at NYU and co-director of the Visualization Imaging and Data Analysis Center at the Tandon School of Engineering) will discuss the challenges involved in capturing and managing computational provenance, and examine the evolution of methods and tools that have been proposed to facilitate transparency and reproducibility.

• Juliana Freire is a Professor of Computer Science and Data Science at New York University and co-directs the Visualization Imaging and Data Analysis Center (VIDA) at the Tandon School of Engineering. She was the elected chair of the ACM Special Interest Group on Management of Data (SIGMOD), served as a council member of the Computing Research Association’s Computing Community Consortium (CCC), was the NYU lead investigator for the Moore-Sloan Data Science Environment, and served as a member of the National Academies Committee  on Reproducibility and Replicability in Science. She develops methods and systems that enable a wide range of users to obtain trustworthy insights from data. This spans topics in large-scale data analysis and integration, visualization, machine learning, provenance management, and  data discovery, and different application areas, including urban analytics, biomedical research, predictive modeling, and computational reproducibility. Freire has co-authored over 250 technical papers (including 12 award-winning publications), several open-source systems, and is an inventor of 12 U.S. patents. She is a AAAS Fellow,  an ACM Fellow, and a recipient of an NSF CAREER, two IBM Faculty awards, and a Google Faculty Research award.  She received the ACM SIGMOD Contributions Award in 2020. Her research has been funded by the National Science Foundation, DARPA, Department of Energy, National Institutes of Health, Sloan Foundation, Gordon and Betty Moore Foundation, W. M. Keck Foundation, Google, Amazon, AT&T Research, Microsoft Research, Yahoo! and IBM. She received a B.S. degree in computer science from the Federal University of Ceara (Brazil), and M.Sc. and Ph.D. degrees in computer science from the State University of New York at Stony Brook.

Register for the Computational Reproducibility webinar.

Past Events

Past Birds of a Feather

• • July 25, 2024 at PEARC24: Reproducibility of Computational Research Community of Practice.
  • July 26, 2023 at PEARC23: Reproducibility of Computational Research: Birds of a Feather session at , July 26, 2023.
  • Nov 15, 2022 at Supercomputing Conference SC22: Reproducibility and Trustworthiness of Computational Research.
  • July 12, 2022 at PEARC22: Reproducibility and Trustworthiness of Scientific Research. Abstract.

Past Webinars

• • SGX3 Webinar: Reproducibility of Computational Research – A Community of Practice