Data Science Coast to Coast Seminar Series

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Data Science Coast to Coast Lecture Series is hosted jointly by seven academic data science institutes and provides a unique opportunity to foster a broad-reaching data science community. Speakers include important figures in data science who will provide insight on the transformative use of data science in traditional research disciplines, future breakthroughs in data science research, data science entrepreneurship, and advocacy and national policies for a data-enabled and just society. The series will also include faculty members and postdoctoral fellows at the seven host universities whose research spans the theory and methodology of data science, and their application in arts and humanities, engineering, biomedical, natural, physical and social sciences.

Hosted by: Institute for Data Intensive Engineering and Science at John Hopkins, NYU Center for Data Science, Ken Kennedy Institute at Rice University, Stanford Data Science, Berkeley Institute for Data Science, Michigan Institute for Data Science, and the eScience Institute at University of Washington


  • Laure Zanna, Professor of Mathematics & Atmosphere/Ocean Science, New York University and Miguel Jimenez-Urias, Postdoctoral Fellow, Earth and Planetary Sciences, Johns Hopkins University (June 16, 2021)
    • Laure. Zanna presents "Blending Machine Learning and Physics to Improve Climate Models"
    • Miguel Jimenez-Urias presents "Oceanic Stirring and Mixing of Passive Scalars: A Novel Closure"

  • Rosemary Gillespie, Professor & Schlinger Chair in Systematic Entomology, University of California, Berkeley and Shelly Trigg, Data Science Postdoctoral Fellow, University of Washington (May 19, 2021)
    • Rosemary Gillespie presents "Data Science to Measure the Natural World"
    • Shelly Trigg presents "Diversity in Animal Response to Environmental Change"

  • H.V. Jagadish, Director of Michigan Institute for Data Science and Professor of Computer Science and Engineering, University of Michigan and Ciera Martinez, Biodiversity and Environmental Sciences Lead, Berkeley Institute for Data Science (April 21, 2021)
    • H.V. Jagadish presents "Data Equity: A Core Requirement for Responsible Data Science"
    • Ciera Martinez presents "Open Science in the Wild: Principles to Build Reproducible and Collaborative Data Analysis Workflows"

  • Arya Farahi, Michigan Data Science Fellow, University of Michigan and Kate Starbird, Associate Professor of Human-Centered Design and Engineering, University of Washington (April 8, 2021)
    • Arya Farahi presents "Quantifying and Mitigating Sources of Bias in a Decision-Support System"
    • Kate Starbird presents "Revealing the “Big Lie”: Methodological Innovation for Rapid Response to Online Disinformation"

  • Lydia Kavraki, Director of the Ken Kennedy Institute and Professor of Computer Science, Rice University and Angela Radulescu, Moore-Sloan Faculty Fellows, Center for Data Science, New York University (Mar 17, 2021)
    • Lydia Kavraki presents "Robotics in the Data Science Era"
    • Angela Radulescu presents "Towards Naturalistic Task Representation in Health and Disease"