Building an open platform for research and education in data science with Project Jupyter - DLS Talk by Fernando Perez, Lawrence Berkeley National Laboratory

Thursday, February 15, 2018 | 3:30pm - 5:00pm
Hugh Dempster Pavilion - Room 110, 6245 Agronomy Rd.

Speaker:  Fernando Perez, Lawrence Berkeley National Laboratory

Host:  Mark Greenstreet, UBC Computer Science


Project Jupyter, evolved from the IPython environment, provides a platform for interactive computing that is widely used today in research, education, journalism and industry.  The core premise of the Jupyter architecture is to design tools around the experience of interactive computing.  It provides an environment, protocol, file format and libraries optimized for the computational process when there is a human in the loop, in a live iteration with ideas and data assisted by the computer.

I will discuss both how the architecture of Jupyter supports a variety of workflows that are central to the processes of research and education. In particular, Jupyter supports reproducible scientific research and the communication of data-intensive narratives both within the scholarly community and with broader audiences.  By providing tools that can benefit research scientists as well as media practitioners and journalists, we hope to contribute to a more informed debate in society in domains where data, computation and science are key.


Fernando PĂ©rez is an assistant professor in Statistics at UC Berkeley and a Faculty Scientist in the Department of Data Science and Technology at Lawrence Berkeley National Laboratory.  After completing a PhD in particle physics at the University of Colorado at Boulder, his postdoctoral research in applied mathematics centered on the development of fast algorithms for the solution of partial differential equations in multiple dimensions.  Today, his research focuses on creating tools for modern computational research and data science across domain disciplines, with an emphasis on high-level languages, interactive and literate computing, and reproducible research.  He created IPython while a graduate student in 2001 and co-founded its successor, Project Jupyter.  The Jupyter team collaborates openly to create the next generation of tools for human-driven computational exploration, data analysis, scientific insight and education.

He is a National Academy of Science Kavli Frontiers of Science Fellow and a Senior Fellow and founding co-investigator of the Berkeley Institute for Data Science.  He is a co-founder of the NumFOCUS Foundation, and a member of the Python Software Foundation.  He is the recipient of the 2012 Award for the Advancement of Free Software from the Free Software Foundation.

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Speaker Affiliation: Lawrence Berkeley National Laboratory
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