BIDS at SciPy 2016

Ali Ferguson / July 18, 2016

Last week, several BIDS fellows and members headed down to Austin, TX, for SciPy 2016, the 15th annual Scientific Computing with Python conference. The general purpose of SciPy is to bring industry, academia, and government participants together to highlight their work, learn from Python power users, and collaborate on code development.

ImageXD: Image Processing across Domains

Kevin Koy / June 22, 2016

By Kevin Koy and Ariel Rokem Incredible advances are being made in image processing techniques and tools, but the researchers who use them typically don’t have the opportunity to communicate with others who work on similar problems in different domains. ImageXD was founded by Berkeley and Washington partners from the Moore-Sloan Data Science Environments (MSDSE) to address these challenges.

Developing a Feel It, Smell It, Touch It Analytics

/ June 4, 2016

In this blog post segment for, Laura Nelson uses sports analytics as a starting point to call for a critical feminist computational social science.  It appeared in's blog post entitled "Forum on Data Analytics and Inclusivity, Part 1" posted by Brayden King on June 4, 2016.

Another BIDS Data Science Faire in the Books

Ali Ferguson / May 6, 2016

Earlier this week, we held our third annual Data Science Faire to celebrate data science at BIDS and UC Berkeley. Like last year, we invited poster/demo presenters from around campus to showcase their data science projects, welcoming participants from Research IT, Digital Humanities, the Space Sciences Laboratory, the California Digital Libary, and many more.

Algorithms to Live By: The Computer Science of Human Decisions

/ April 28, 2016

BIDS senior fellow Tom Griffiths recently co-authored a book (Algorithms to Live By: The Computer Science of Human Decisions) that "combines the best of computer science and human intuition to head off an epidemic of too many choices and not enough time." Continue reading to learn more. by Yasmin Anwar, UC Berkeley Media Relations Information overload and “fear of missing out” may rank among the biggest contributors to chronic indecision. But help is at hand.

Call for Reproducibility Workflows

Cyrus Dioun / April 26, 2016

BIDS fellows Cyrus Dioun and Garret Christensen are seeking reproducibility workflows from social scientists throughout academia. 

Call for Posters and Exhibits | BIDS Spring 2016 Data Science Faire

/ March 31, 2016

This year’s Data Science Faire (May 3) will feature poster/demo exhibits from students and researchers on campus. If you have been doing work related to data science (e.g., conducting a data-intensive project, running an open source meetup on campus, developing tools to enable reproducible science, etc.) and would like to showcase your efforts at the Data Science Faire, we'd love to have you.

With Data, Bigger Might Not Always Be Better

Jasmine Nirody / March 21, 2016

Every conversation I’ve heard about what it means to be a data scientist consists of tons of ideas but no consensus. While it seems like nobody can agree on the sufficient conditions for obtaining this illustrious title, a lot of people are vehement about a necessary one: being a data scientist means you work with big data.

Computational Thinking: I Do Not Think It Means What You Think It Means

Lorena Barba / March 8, 2016

BIDS visiting scholar Lorena Barba posted a great blog post on computational thinking and was kindly willing to let us cross-post on our blog. Check it out below.