Data Science Lecture Series: A Case Study in Reproducible Data Science: Measuring and Modeling Human Brain Connectivity | February 13, 2015 | 1:00–2:30 p.m. | 190 Doe Library
Speaker: Ariel Rokem, Postdoctoral Scholar, Stanford University
Sponsors: Berkeley Institute for Data Science and Data, Society, and Inference Seminar
Data Science Lecture Series: Maximizing Human Potential Using Machine Learning-Driven Applications
Lecture | September 19, 2014 | 1:00-2:30 p.m. | Sutardja Dai Hall, Banatao Auditorium
Speaker/Performer: Vivienne Ming, Chief Scientist at Gild
Sponsors: Berkeley Institute for Data Science, Data, Society and Inference Seminar
BIDS senior fellow and research associate Fernando Perez discusses the "career problem" in academia—the challenges academics at the intersection of methods and domain science face for career advancement—and how BIDS will serve as collaborative hub to help work through and overcome these challenges.
BIDS senior fellow Joshua Bloom describes data science efforts at Berkeley, with a particular focus on teaching and the new Berkeley Institute for Data Science (BIDS), funded by the Moore and Sloan Foundations. BIDS will be a space for the open and interdisciplinary work that is typical of the data science community. In the creation of BIDS, open source scientific tools for data science, specifically the SciPy ecosystem, played an important role.
On December 12, 2013, the Director for the new Berkeley Institute for Data Science, Nobel Laureate Saul Perlmutter, was joined by Vicki Chandler from the Gordon and Betty Moore Foundation, UC Berkeley's Chancellor Nicholas Dirks, Tim O'Reilly, Founder and CEO of O'Reilly Media, and Peter Norvig, Director of Research at Google, for the launch event celebrating the establishment of the new Institute.
Published on Dec 13, 2013
Moderated by Joshua Bloom, Astronomy
Deborah Agarwal, Lawrence Berkeley National Laboratory
Cathryn Carson, Social Sciences; D-Lab
One of the major scientific challenges of our time is to understand how the brain works. Recently, researchers have attempted to answer one of the important questions in computational neuroscience: Can the vast quantities of high-dimensional neuroscience data available today be used to decode brain activities?
