Brought to you by NumFOCUS Foundation and O’Reilly Media
The official Jupyter Conference
Aug 21-22, 2018: Training
Aug 22-24, 2018: Tutorials & Conference
New York, NY
Julia Lane

Julia Lane
Professor, Center for Urban Science and Progress and Wagner School, NYU

Julia Lane is a professor at the NYU Wagner Graduate School of Public Service and the NYU Center for Urban Science and Progress as well as a NYU provostial fellow for innovation analytics. Previously, Julia was a senior managing economist and institute fellow at American Institutes for Research, where she cofounded the Institute for Research on Innovation and Science (IRIS) at the University of Michigan. Over her career, Julia has held positions at the National Science Foundation, the Urban Institute, the World Bank, American University, and NORC at the University at Chicago.

Sessions

4:10pm–4:50pm Thursday, August 23, 2018
JupyterCon Business Summit
Location: Concourse A: Business Summit
Julia Lane (Center for Urban Science and Progress and Wagner School, NYU)
Average rating: *****
(5.00, 2 ratings)
Government agencies have found it difficult to serve taxpayers because of the technical, bureaucratic, and ethical issues associated with access and use of sensitive data. Julia Lane explains how the Coleridge Initiative has partnered with Jupyter to design ways that can address the core problems such organizations face. Read more.
5:00pm–5:40pm Thursday, August 23, 2018
JupyterCon Business Summit
Location: Concourse A: Business Summit
David Schaaf (Capital One), Julia Lane (Center for Urban Science and Progress and Wagner School, NYU), Dan Romuald Mbanga (Amazon Web Services), Dave Stuart (Department of Defense ), Michael Li (The Data Incubator), Pramit Choudhary (Oracle(Datascience.com))
Average rating: ****.
(4.67, 3 ratings)
Join in for the Business Summit's roundtable discussion with participation from IBM, Capital One, the DoD, AWS, Oracle, and others. Speakers will discuss important issues in our current environment—everything from compliance and GDPR to ML models. Read more.