News

Blogging Hurts—Why Academic Researchers Are Reluctant to Blog and How to Get Them Interested in Contributing Content

Julia Astro: Enabling Next-Generation Analysis in Astronomy

New DOE Office of Science Support for CAMERA to Develop Computational Mathematics for Experimental Facilities Research

Contact: Linda Vu, +1 510 495 2402, lvu@lbl.gov Experimental science is evolving. With the advent of new technology, scientific facilities are collecting data at increasing rates and higher resolution. However, making sense of this data is becoming a major bottleneck. New mathematics and algorithms are needed to extract useful information from these experiments.  

Fall 2015 Data Science Lecture Series Lineup

We have a great lineup of speakers from industry and academia for our Data Science Lecture Series. The lectures are held Fridays, 1:00–2:30 p.m. in 190 Doe Library (one-hour lectures followed by 30 minutes for Q&A). Please keep an eye on our Events page to learn more about each of these lectures as detailed information becomes available.

Welcoming BIDS 2015 Data Science Fellows

We are thrilled to introduce our 2015 cohort of data science fellows! With diverse research backgrounds and experiences, the new Fellows will complement BIDS founding group in driving data science innovations and enhancing collaborations across UC Berkeley and beyond. Please join us in welcoming them:

BIDS Fellow Katy Huff Releases New Book: Effective Computation in Physics

BIDS at SciPy 2015: Marking a Year of Success

This past Sunday marked the end to the successful 14th annual Scientific Computing with Python Conference, more commonly known as SciPy. Roughly 600 attendees from more than 330 organizations throughout the world gathered in Austin, TX, to showcase and discuss their Python-centric mathematics, science, and engineering projects. Among these individuals were several BIDS fellows, staff members, and affiliates.

Project Jupyter Awarded $6M to Expand Collaborative Data Science Software

By Sarah Yang, UC Berkeley Media Relations A powerful, interactive tool popular among academics and scientists who wrestle with large datasets in multiple formats is getting a big infusion of support to broaden its capabilities for collaborative data science and to reach ever wider audiences

Scaling Up Content Analysis: Text Thresher Joins Forces with Hypothes.is and Crowdcrafting

Toward Reproducible Science—A Quick Overview of the Recent BIDS Reproducibility Workshop

On May 21–22, BIDS hosted a Reproducibility Workshop. We had about 35 participants, including several BIDS fellows and staff as well as representatives from our NYU and UW partners. In addition, there were students, faculty, and staff from numerous departments and organizations from all over the campus.